Screen-Based Simulation in Nursing School: Help Use and Self-Regulated Learning
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| Title: | Screen-Based Simulation in Nursing School: Help Use and Self-Regulated Learning |
|---|---|
| Language: | English |
| Authors: | Guillaume Decormeille (ORCID |
| Source: | Applied Cognitive Psychology. 2025 39(2). |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 19 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Foreign Countries, Nursing Education, Nursing Students, Computer Simulation, Computer Assisted Instruction, Self Efficacy, Achievement Gains, Self Management, Independent Study, Cognitive Processes, Difficulty Level, Visual Learning, Aural Learning, Teaching Methods, Program Effectiveness |
| Geographic Terms: | France |
| DOI: | 10.1002/acp.70046 |
| ISSN: | 0888-4080 1099-0720 |
| Abstract: | Screen-based simulation (SBS) can complement traditional nursing courses. We compared the effect of innovative virtual environments not widespread in French nursing schools on self-efficacy, quiz performance, and self-regulated learning behaviors. This quasi-experimental study involved 1183 student nurses. Participants were divided into an experimental group (SBS training; n = 894) and a control group (textual content; n = 289). SBS group performed significantly better than controls (p < 0.001) and improved over time (p < 0.001). Controls performed worse over time (p < 0.001). In the control group, a single medium may have overloaded sensory channels, while SBS spread cognitive load across auditory and visual channels. SBS was more effective than traditional teaching and enhanced self-efficacy. This initial study is encouraging, suggesting further investigation into SBS in training and the analysis of learning behaviors through digital data. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1468393 |
| Database: | ERIC |
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| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwEbww_MULj1H5oQwuS2HobFAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDJr9kth7wrLiEsOpLQIBEICBm511h_chey5vDP6jwKTfvR9Pn1xL3xGjBlhZKbDaEA_3PD5clDDojdk5g_MtEQQr3WsOI6zOgMeeuq3kb0NEksZ5-5Q937kgAci3a8p8khQ7NlmsEglxD-3ZDE1fGfl_GmVz0O9Q8GCea-fKYlsQfLVHrwc9USN1DDDtbUhZ9zeUV-zhXqxPVPjgbxJulWi4tjYRoBFqWLF3TdQO Text: Availability: 1 Value: <anid>AN0184623592;bu801mar.25;2025Apr23.01:41;v2.2.500</anid> <title id="AN0184623592-1">Screen‐Based Simulation in Nursing School: Help Use and Self‐Regulated Learning </title> <p>Screen‐based simulation (SBS) can complement traditional nursing courses. We compared the effect of innovative virtual environments not widespread in French nursing schools on self‐efficacy, quiz performance, and self‐regulated learning behaviors. This quasi‐experimental study involved 1183 student nurses. Participants were divided into an experimental group (SBS training; n = 894) and a control group (textual content; n = 289). SBS group performed significantly better than controls (p &lt; 0.001) and improved over time (p &lt; 0.001). Controls performed worse over time (p &lt; 0.001). In the control group, a single medium may have overloaded sensory channels, while SBS spread cognitive load across auditory and visual channels. SBS was more effective than traditional teaching and enhanced self‐efficacy. This initial study is encouraging, suggesting further investigation into SBS in training and the analysis of learning behaviors through digital data.</p> <p>Keywords: nursing student; screen‐based simulator; self‐efficacy; self‐regulated learning; self‐regulation profiles</p> <hd id="AN0184623592-2">Introduction</hd> <p>The use of virtual environments with learning content is becoming increasingly widespread (Brubacher et al. [<reflink idref="bib18" id="ref1">18</reflink>]; Kim et al. [<reflink idref="bib65" id="ref2">65</reflink>]; Ko et al. [<reflink idref="bib69" id="ref3">69</reflink>]; Park et al. [<reflink idref="bib111" id="ref4">111</reflink>]; Segal et al. [<reflink idref="bib135" id="ref5">135</reflink>]; Sim et al. [<reflink idref="bib138" id="ref6">138</reflink>]; Haginoya et al. [<reflink idref="bib50" id="ref7">50</reflink>]). In healthcare education, screen‐based simulation (SBS), serious games, and web‐based or virtual reality and simulation play an important role in complementing or replacing face‐to‐face training (Roberts et al. [<reflink idref="bib119" id="ref8">119</reflink>]; Verkuyl and Hughes [<reflink idref="bib150" id="ref9">150</reflink>]). The use of SBS (Foronda [<reflink idref="bib43" id="ref10">43</reflink>]; Lioce et al. [<reflink idref="bib79" id="ref11">79</reflink>]) as a virtual modality is well‐referenced in the initial training of nursing students (Guyennet et al. [<reflink idref="bib49" id="ref12">49</reflink>]; Keys et al. [<reflink idref="bib63" id="ref13">63</reflink>]; Maheu‐Cadotte et al. [<reflink idref="bib84" id="ref14">84</reflink>]; Tudor Car et al. [<reflink idref="bib146" id="ref15">146</reflink>]) not least for learning clinical reasoning (Sim et al. [<reflink idref="bib138" id="ref16">138</reflink>]). In addition, the meta‐analysis of Qiao et al. ([<reflink idref="bib115" id="ref17">115</reflink>]) showed that the use of SBS in nursing studies could improve knowledge, performance, and self‐efficacy (see Olaussen et al. [<reflink idref="bib103" id="ref18">103</reflink>]; Qiao et al. [<reflink idref="bib115" id="ref19">115</reflink>]).</p> <p> <emph>Clinical reasoning</emph> is a complex skill that nursing students must acquire during their training (Clemett and Raleigh [<reflink idref="bib30" id="ref20">30</reflink>]) with Macauley et al. [<reflink idref="bib82" id="ref21">82</reflink>] highlighting the challenge for healthcare students. Blanié, Amorim, et al. ([<reflink idref="bib11" id="ref22">11</reflink>]) showed that SBS simulation aids clinical reasoning acquisition in a randomized controlled study. The scenarios were designed for second‐ and third‐year students, not first‐year ones. Personalized clinical reasoning, based on the patient and care context, improves evidence‐based care. It involves the patient's history, pathology, and cognitive faculties (Tanner [<reflink idref="bib143" id="ref23">143</reflink>]), but for novice students, making connections between these elements is difficult. Acquiring patient‐specific clinical reasoning is a delicate skill, primarily learned in clinical practice, though simulation serves as an alternative (Guyennet et al. [<reflink idref="bib49" id="ref24">49</reflink>]; Macauley et al. [<reflink idref="bib82" id="ref25">82</reflink>]; Olaussen et al. [<reflink idref="bib103" id="ref26">103</reflink>]).</p> <p>Simulation, especially virtual simulation like SBS, is proving effective in teaching clinical reasoning (Alshehri et al. [<reflink idref="bib3" id="ref27">3</reflink>]). However, there is a wide variation in the quality of SBS used in nursing education (Sim et al. [<reflink idref="bib138" id="ref28">138</reflink>]) making effectiveness assessments challenging. Some studies lack a control group, which impacts internal validity (Luo et al. [<reflink idref="bib81" id="ref29">81</reflink>]; Tan et al. [<reflink idref="bib142" id="ref30">142</reflink>]). In France, an SBS developer worked with 27 nursing schools in Nouvelle Acquitaine to design a complete and adapted digital software package of teaching scenarios based on an official list of nursing skills, improving ecological validity. However, other schools have not yet tested these SBSs. The current study is innovative because it includes a control group of schools that do not use SBS and analyzes actual learner behavior rather than relying on self‐reporting (e.g., Huet et al. [<reflink idref="bib55" id="ref31">55</reflink>]).</p> <p>Learning in a computer‐assisted digital environment such as SBS requires individual skills such as self‐regulated learning (SRL) and the ability to gauge one's own learning process (Panadero et al. [<reflink idref="bib110" id="ref32">110</reflink>]; Wong et al. [<reflink idref="bib154" id="ref33">154</reflink>]), including its cognitive, metacognitive and motivational components (Syal and Nietfeld [<reflink idref="bib141" id="ref34">141</reflink>]). Students often fail to effectively self‐regulate their learning (Aleven et al. [<reflink idref="bib2" id="ref35">2</reflink>]), which can negatively affect their performance. It is therefore important to identify the factors affecting SRL. One factor that has already been identified is <emph>self‐efficacy</emph> (e.g., Pajares and Schunk [<reflink idref="bib107" id="ref36">107</reflink>]). This refers to individuals' beliefs in their ability to successfully perform a specific task. The ability to appropriately self‐regulate one's learning depends on the degree of self‐efficacy (Aleven et al. [<reflink idref="bib2" id="ref37">2</reflink>]; Huet et al. [<reflink idref="bib58" id="ref38">58</reflink>]; Panadero et al. [<reflink idref="bib110" id="ref39">110</reflink>]). Moreover, as Zimmerman and Schunk ([<reflink idref="bib164" id="ref40">164</reflink>]) demonstrated, the relationship between self‐regulation and self‐efficacy is reciprocal.</p> <p>Several factors have been identified in research on learning with new technologies. In virtual environments, learning can be affected by different extrinsic or intrinsic factors. In reference to Mayer's theory (Mayer et al. [<reflink idref="bib88" id="ref41">88</reflink>]), extrinsic factors can relate to the design or characteristics of the tool (single media or multimedia) (e.g., van Houten‐Schat et al. [<reflink idref="bib53" id="ref42">53</reflink>]). In the current study, SBS are considered multimedia, integrating several delivery channels such as images, text, and voice. The intrinsic factors that influence learning are related to the learner, such as SRL, help‐seeking behavior (revealed by analysis of digital trace data), self‐efficacy, and confidence judgments. The main objective of the present study was to assess the impact of SBS versus traditional education on self‐efficacy during the learning process, on confidence judgment accuracy, and on learning performance.</p> <hd id="AN0184623592-3">Usefulness of SBS for Learning</hd> <p>Simulation‐based scenarios (SBS) provide a multimedia environment and represent a key teaching modality in healthcare education. This interactive technology replicates clinical settings in 3D, offering an immersive experience that strengthens students' theoretical knowledge (Koivisto et al. [<reflink idref="bib70" id="ref43">70</reflink>]; Wright et al. [<reflink idref="bib155" id="ref44">155</reflink>]) and enhances experiential learning through simulated practice (Kolb [<reflink idref="bib73" id="ref45">73</reflink>]; Verkuyl et al. [<reflink idref="bib149" id="ref46">149</reflink>]). To maximize effectiveness, educational content must align with learners' training levels, and the 3D environment—developed with tools like Unity—should closely mirror real‐world settings to support immersion and didactic transposition (Koivisto et al. [<reflink idref="bib70" id="ref47">70</reflink>]; Rogalski [<reflink idref="bib121" id="ref48">121</reflink>]).</p> <p>Not all platforms offering simulation‐based solutions are supported by a Learning Management System (LMS), which enables the monitoring of students' individual learning activities through digital traces (e.g., Kim et al. [<reflink idref="bib65" id="ref49">65</reflink>]). When SBS adheres to development standards, this tracking becomes a significant advantage. Cant and Cooper's ([<reflink idref="bib25" id="ref50">25</reflink>]) meta‐analysis emphasized the necessity of rigorous scenarios and study designs to enable meaningful comparisons, with effect size serving as a key evaluation criterion. Although SBS technologies began to emerge in 2017, their development accelerated following the COVID‐19 pandemic in 2020, with numerous digital solutions appearing. However, in France, SBS remains underdeveloped in nursing education compared to the United States (Blanié, Rihane, et al. [<reflink idref="bib12" id="ref51">12</reflink>]; Decormeille et al. [<reflink idref="bib36" id="ref52">36</reflink>]; Sim et al. [<reflink idref="bib138" id="ref53">138</reflink>]).</p> <p>A critical benefit of this digital environment is its ability to analyze students' learning behaviors via digital traces rather than relying solely on self‐reports. This approach addresses the common gap between self‐reported intentions and actual behavior (Gollwitzer et al. [<reflink idref="bib45" id="ref54">45</reflink>]). In this study, we used digital traces to profile students based on their SRL behaviors (Shirah and Sidney [<reflink idref="bib137" id="ref55">137</reflink>]).</p> <p>Regarding the cognitive processes and mental representations involved in multimedia learning, Mayer ([<reflink idref="bib86" id="ref56">86</reflink>]) stated that learners retain more if the information is provided through <emph>two channels</emph> (i.e., visual and verbal). It is called the modality effect, which refers to a cognitive load learning phenomenon where a mixed‐mode presentation of information (combining both visual and auditory elements) is more effective than presenting the same information in a single mode (either visual or auditory alone). The modality principle enhances working memory by combining auditory and visuospatial processing, increasing capacity compared to using one modality alone (see Castro‐Alonso and Sweller [<reflink idref="bib26" id="ref57">26</reflink>]).</p> <p>To promote learning in digital environments, immersive graphics must closely resemble reality, avoiding cartoon‐like representations (Koivisto et al. [<reflink idref="bib70" id="ref58">70</reflink>]) but this preference may differ for various populations, such as child learners, see Wu et al. ([<reflink idref="bib156" id="ref59">156</reflink>]). This is particularly important for novice healthcare students who struggle to visualize clinical settings. A balance is needed between graphical quality and scenario immersion to prevent over‐ or disimmersion due to errors (Rogalski [<reflink idref="bib122" id="ref60">122</reflink>]). Authentic interactions, including auditory over text‐based ones, enhance didactic transposition (Moreno and Mayer [<reflink idref="bib95" id="ref61">95</reflink>]; Wang et al. [<reflink idref="bib151" id="ref62">151</reflink>]). Encouraging learners to select explanations and access additional content increases engagement and reinforces memory activation (e.g., Goldberg and Cannon‐Bowers [<reflink idref="bib44" id="ref63">44</reflink>]; Vandercruysse et al. [<reflink idref="bib148" id="ref64">148</reflink>]). These strategies aim to stimulate sensory, working, and long‐term memory while supporting metacognitive processes to anchor learning effectively (Blanié, Amorim, et al. [<reflink idref="bib11" id="ref65">11</reflink>]; Rouleau et al. [<reflink idref="bib124" id="ref66">124</reflink>]).</p> <hd id="AN0184623592-4">SBS For Nursing Students in Healthcare Education</hd> <p>As indicated earlier, SBS is a simulation‐based teaching modality (Lioce et al. [<reflink idref="bib79" id="ref67">79</reflink>]). Students interact with a virtual patient by clicking on the questions they want to ask, which are made audible through recorded voices of actors, to increase the immersion. While they are caring for the patient, students have to answer questions (knowledge quizzes) probing their theoretical knowledge. Authenticity is key to helping students make the connections between experiential learning and real‐life practice (Weeks et al. [<reflink idref="bib152" id="ref68">152</reflink>]). SBS promotes their experiential learning (Kolb and Kolb [<reflink idref="bib74" id="ref69">74</reflink>]) and attention (Drummond et al. [<reflink idref="bib38" id="ref70">38</reflink>]), and provides a safe environment where patients and students are free from harm (Borg Sapiano et al. [<reflink idref="bib15" id="ref71">15</reflink>]) during the simulation (Koivisto et al. [<reflink idref="bib72" id="ref72">72</reflink>]).</p> <p>SBS allows nursing students to learn clinical reasoning (Koivisto and Hamari [<reflink idref="bib71" id="ref73">71</reflink>]; Qiao et al. [<reflink idref="bib115" id="ref74">115</reflink>]; Wu et al. [<reflink idref="bib157" id="ref75">157</reflink>]) and decision‐making (Cant and Cooper [<reflink idref="bib24" id="ref76">24</reflink>]; Rouleau et al. [<reflink idref="bib124" id="ref77">124</reflink>]) in real time (Bonnetain et al. [<reflink idref="bib14" id="ref78">14</reflink>]). A review of the literature shows that there is considerable interest in the use of these innovative tools to improve students' outcomes in the field of healthcare (Gorbanev et al. [<reflink idref="bib47" id="ref79">47</reflink>]; Sipiyaruk et al. [<reflink idref="bib139" id="ref80">139</reflink>]). However, it is essential to compare the educational content and interfaces of these solutions, but their heterogeneity complicates the interpretation and conclusion of meta‐analyses due to their limited comparability (Park et al. [<reflink idref="bib111" id="ref81">111</reflink>]). SBS has the advantage of giving nursing students an opportunity to gauge their prior knowledge (Coyne et al. [<reflink idref="bib34" id="ref82">34</reflink>]) through their performances on the knowledge quizzes (Cooper and Bogossian [<reflink idref="bib32" id="ref83">32</reflink>]), and allows tutors to monitor learners and measure their performance (Bergeron [<reflink idref="bib10" id="ref84">10</reflink>]). Analysis of the digital traces left by learners also makes it possible to assess learners' SRL behaviors. Learning with SBS requires students to self‐regulate their learning, insofar as it is done autonomously.</p> <hd id="AN0184623592-5">SRL</hd> <p>Learning in a computer‐mediated digital environment, such as SBS, requires individual skills like SRL and enjoyment of the learning process (Panadero [<reflink idref="bib109" id="ref85">109</reflink>]). SRL involves students actively regulating their cognition, motivation, and behavior to achieve goals (Pintrich [<reflink idref="bib112" id="ref86">112</reflink>]; Schunk and Zimmerman [<reflink idref="bib131" id="ref87">131</reflink>]; Zimmerman and Moylan [<reflink idref="bib163" id="ref88">163</reflink>]). This skill is crucial in online learning, where learners take full responsibility for their progress (Cosnefroy [<reflink idref="bib33" id="ref89">33</reflink>]). According to Zimmerman and Moylan ([<reflink idref="bib163" id="ref90">163</reflink>]), self‐regulated learners are motivationally, metacognitively, and behaviorally active learners who manage their own learning. A main motivational factor affecting self‐regulation and performance is self‐efficacy beliefs (Bandura [<reflink idref="bib7" id="ref91">7</reflink>]; Bouffard‐Bouchard et al. [<reflink idref="bib16" id="ref92">16</reflink>]; Multon et al. [<reflink idref="bib97" id="ref93">97</reflink>]; Pajares and Valiante [<reflink idref="bib108" id="ref94">108</reflink>]; Stajkovic and Luthans [<reflink idref="bib140" id="ref95">140</reflink>]; Travis et al. [<reflink idref="bib145" id="ref96">145</reflink>]), including academic performance in online environments (Yokoyama [<reflink idref="bib161" id="ref97">161</reflink>]). According to Bouffard‐Bouchard et al. ([<reflink idref="bib16" id="ref98">16</reflink>]), the higher students' self‐efficacy beliefs, the better their self‐regulation processes and vice versa, and these beliefs are associated with better performance. The latter requires a range of metacognitive skills (Azevedo et al. [<reflink idref="bib5" id="ref99">5</reflink>]; Huet et al. [<reflink idref="bib58" id="ref100">58</reflink>]; Huet and Mariné [<reflink idref="bib57" id="ref101">57</reflink>]), including appropriate help‐seeking (Karabenick and Newman [<reflink idref="bib62" id="ref102">62</reflink>]; Puustinen [<reflink idref="bib113" id="ref103">113</reflink>]). Seeking and using help is a complex self‐regulated strategy that is regarded as an active learning process (Burgues et al. [<reflink idref="bib20" id="ref104">20</reflink>]; Finney et al. [<reflink idref="bib42" id="ref105">42</reflink>]; Mulet et al. [<reflink idref="bib96" id="ref106">96</reflink>]). It involves the use of help in an interactive learning environment as and when required (Karabenick and Newman [<reflink idref="bib62" id="ref107">62</reflink>]). It is regarded as a metacognitive strategy that promotes learning (Newman [<reflink idref="bib101" id="ref108">101</reflink>]; Puustinen [<reflink idref="bib113" id="ref109">113</reflink>]; Ryan and Pintrich [<reflink idref="bib127" id="ref110">127</reflink>]; Zimmerman and Martinez‐Pons [<reflink idref="bib162" id="ref111">162</reflink>]).</p> <p>Learners seek help to obtain information from formal and informal sources to acquire and adapt their knowledge and skills (Karabenick and Berger [<reflink idref="bib61" id="ref112">61</reflink>]). The help can be available while the learning task is being carried out, or after receiving error feedback (e.g., Huet et al. [<reflink idref="bib56" id="ref113">56</reflink>]) to help the learner understand the error and avoid repeating it (e.g., Huet et al. [<reflink idref="bib58" id="ref114">58</reflink>]). According to Butler and Neuman ([<reflink idref="bib22" id="ref115">22</reflink>]), there are two forms of help‐seeking, which vary in the extent to which they promote learning: executive and instrumental help‐seeking. Students may also exhibit help‐seeking avoidance. <emph>Avoidance of help</emph> refers to students who are aware they need help but who do not seek it, while <emph>executive help</emph> characterizes students who ask for help but inappropriately (Nelson‐Le Gall [<reflink idref="bib100" id="ref116">100</reflink>]). The latter's aim is to receive the readymade answer without the effort of looking for it on their own. <emph>Instrumental help</emph> is defined as the minimal amount of help required for students to accomplish the task alone. In this sense, it is assumed to be the most favorable for learning (Huet et al. [<reflink idref="bib55" id="ref117">55</reflink>]; Nelson‐Le Gall [<reflink idref="bib100" id="ref118">100</reflink>]; Puustinen [<reflink idref="bib113" id="ref119">113</reflink>]). Schworm and Gruber ([<reflink idref="bib134" id="ref120">134</reflink>]) showed that the more students ask a teacher questions via a forum (instrumental help), the better their performance. This result highlighting the positive effect of help‐seeking on academic outcomes has been replicated by several authors (e.g., Clarebout and Elen [<reflink idref="bib29" id="ref121">29</reflink>]; Jiang et al. [<reflink idref="bib60" id="ref122">60</reflink>]; Schwonke et al. [<reflink idref="bib133" id="ref123">133</reflink>]). However, the decision to use the help that has been sought depends on self‐efficacy. According to Schneider and Preckel ([<reflink idref="bib128" id="ref124">128</reflink>]), self‐efficacy is one of the most important nonintellectual determinants of performance, with which it has been shown to be positively correlated (Klassen and Usher [<reflink idref="bib68" id="ref125">68</reflink>]).</p> <p>Previous studies have demonstrated that self‐efficacy evolves with learning experience and increases as individuals gain more experience (Kher et al. [<reflink idref="bib64" id="ref126">64</reflink>]). Bandura ([<reflink idref="bib7" id="ref127">7</reflink>]) emphasized that self‐efficacy is malleable and can be positively influenced by experience. Maricuțoiu and Sulea ([<reflink idref="bib85" id="ref128">85</reflink>]) observed that an increase in self‐efficacy over a semester was associated with greater engagement, although evidence of short‐term changes remains limited. With experience, individuals become more confident in their ability to complete specific tasks, viewing new challenges, such as learning activities, as opportunities rather than threats (Bandura [<reflink idref="bib7" id="ref129">7</reflink>]; Pajares and Schunk [<reflink idref="bib107" id="ref130">107</reflink>]; Schwarzer and Jerusalem [<reflink idref="bib132" id="ref131">132</reflink>]).</p> <p>Qiao et al. ([<reflink idref="bib115" id="ref132">115</reflink>])'s meta‐analysis revealed that individuals exposed to SBS report higher self‐efficacy levels than controls (e.g., Abusubhiah et al. [<reflink idref="bib1" id="ref133">1</reflink>]; Olaussen et al. [<reflink idref="bib103" id="ref134">103</reflink>]). Furthermore, metacognitive monitoring, which reflects learners' ability to evaluate their progress and generate performance judgments, is critical for SRL (Huet et al. [<reflink idref="bib58" id="ref135">58</reflink>]; Roebers et al. [<reflink idref="bib120" id="ref136">120</reflink>]). These probabilistic judgments, occurring before, during, or after tasks, form the foundation of control processes in SRL (Schraw [<reflink idref="bib130" id="ref137">130</reflink>]). Accurate self‐monitoring and adaptive strategy use are essential for becoming a self‐regulated learner.</p> <p>Nelson‐Le Gall ([<reflink idref="bib100" id="ref138">100</reflink>]) and Nelson and Ketelhut ([<reflink idref="bib98" id="ref139">98</reflink>]), building on the vulnerability hypothesis (Tessler and Schwartz [<reflink idref="bib144" id="ref140">144</reflink>]), argue that students with low self‐efficacy seek less help compared to those with high self‐efficacy. Conversely, the inverted U‐curve hypothesis suggests that students with moderate self‐efficacy are more likely to seek help, while those with very low or very high self‐efficacy avoid it—either to maintain an impression of ability or due to overconfidence (Pajares et al. [<reflink idref="bib106" id="ref141">106</reflink>]; Rosen [<reflink idref="bib123" id="ref142">123</reflink>]). Both hypotheses are largely supported by self‐reported measures of help‐seeking intentions. Finally, the consistency hypothesis (Tessler and Schwartz [<reflink idref="bib144" id="ref143">144</reflink>]) posits that students with high self‐efficacy are less likely to seek help, as doing so would conflict with their self‐perceptions (Butler [<reflink idref="bib21" id="ref144">21</reflink>]; Huet et al. [<reflink idref="bib58" id="ref145">58</reflink>]; Nelson‐Le Gall [<reflink idref="bib100" id="ref146">100</reflink>]). This hypothesis has been confirmed primarily through behavioral indicators, such as the frequency of clicks on help buttons.</p> <p>The relationship between self‐efficacy and help‐seeking appears to depend on the measurement used. Research has predominantly focused on self‐efficacy and help‐seeking intentions, with fewer studies on actual help‐seeking behaviors. Existing studies generally support the consistency hypothesis, linking high self‐efficacy to reduced help‐seeking (Butler [<reflink idref="bib21" id="ref147">21</reflink>]; Nelson‐Le Gall [<reflink idref="bib100" id="ref148">100</reflink>]; Williams and Takaku [<reflink idref="bib153" id="ref149">153</reflink>]). Puustinen and Winnykamen ([<reflink idref="bib114" id="ref150">114</reflink>]) found that children with low self‐efficacy sought instrumental help more than executive help, achieving similar performance levels to high self‐efficacy peers while enhancing their self‐efficacy for future tasks. Overall, evidence suggests that help‐seeking can positively influence self‐efficacy (Puustinen and Winnykamen [<reflink idref="bib114" id="ref151">114</reflink>]).</p> <p>Highly self‐regulated learners can adjust their strategies based on metacognitive judgments, such as confidence judgments—retrospective assessments of answer accuracy after completing a task (Bouffard‐Bouchard and Pinard [<reflink idref="bib17" id="ref152">17</reflink>]; Dinsmore and Parkinson [<reflink idref="bib37" id="ref153">37</reflink>]; Schraw [<reflink idref="bib129" id="ref154">129</reflink>]). These judgments are critical for learning, as inaccurate judgments may lead to an illusion of knowing, where learners believe they have mastered content and prematurely halt further learning.</p> <p>Accuracy reflects the difference between actual and estimated performance, both measured on the same scale (Dunlosky et al. [<reflink idref="bib39" id="ref155">39</reflink>]; Fiacconi and Dollois [<reflink idref="bib41" id="ref156">41</reflink>]; Hu et al. [<reflink idref="bib54" id="ref157">54</reflink>]). Actual performance is derived from digital trace analysis. Self‐regulated learners are generally more accurate in self‐assessment, a key indicator of progress (Schraw [<reflink idref="bib129" id="ref158">129</reflink>]). Performance estimation biases include underestimation (negative values, underconfidence) and overestimation (positive values, overconfidence) as outlined by Yates ([<reflink idref="bib159" id="ref159">159</reflink>]). These biases are determined by the discrepancy between self‐assessed and actual performance (Baars et al. [<reflink idref="bib6" id="ref160">6</reflink>]; Gonida and Leondari [<reflink idref="bib46" id="ref161">46</reflink>]). While the magnitude of these biases varies, they tend to remain stable over time, shaped by experience and training (Leonesio and Nelson [<reflink idref="bib78" id="ref162">78</reflink>]; Mengelkamp and Bannert [<reflink idref="bib91" id="ref163">91</reflink>]). Importantly, weaker performers demonstrate less accurate performance monitoring compared to their stronger counterparts (Schraw [<reflink idref="bib129" id="ref164">129</reflink>]). Qiao et al. ([<reflink idref="bib115" id="ref165">115</reflink>]) found that nonimmersive virtual reality boosts nursing students' confidence judgments more than traditional methods.</p> <hd id="AN0184623592-6">The Present Study and Hypotheses</hd> <p>The present study compared participants exposed to SBS (experimental group) with students exposed to traditional education (i.e., same learning content, but in a single medium; control group). Its five aims were to (<reflink idref="bib1" id="ref166">1</reflink>) study the effect of group on progress in training and performance; (<reflink idref="bib2" id="ref167">2</reflink>) examine the relationship between self‐efficacy and performance according to group; (<reflink idref="bib3" id="ref168">3</reflink>) establish students' SRL profiles according to their use of help; (<reflink idref="bib4" id="ref169">4</reflink>) verify whether the relationship between self‐efficacy and use of help favors the consistency, vulnerability, or U‐curve hypothesis; and (<reflink idref="bib5" id="ref170">5</reflink>) examine the effect of group on confidence judgment accuracy. Based on the evidence above, we tested the predictions of five hypotheses:</p> <p> <bold>H1.</bold> <emph>The SBS group (experimental group) would perform better than the control group, and the gap between the two would increase across learning</emph>;</p> <p> <bold>H2.</bold> <emph>Performance would improve with self‐efficacy and experience, especially in the SBS group</emph>;</p> <p> <bold>H3.</bold> <emph>Students who used instrumental help would perform better than those who used executive help or who avoided seeking help</emph>;</p> <p> <bold>H4.</bold> <emph>Students with high self‐efficacy would be less likely to use help than those with low self‐efficacy, as admitting that they needed help would not be consistent with their self‐perceptions, according to the consistency hypothesis</emph>;</p> <p> <bold>H5.</bold> <emph>Confidence judgments would be higher and more accurate in the experimental group than in the control group</emph>.</p> <hd id="AN0184623592-7">Method</hd> <p>Our protocol allowed us to identify SRL profiles, which are normally the preserve of psychology studies (e.g., Syal and Nietfeld [<reflink idref="bib141" id="ref171">141</reflink>]; Wu [<reflink idref="bib158" id="ref172">158</reflink>]). The inclusion of an intermediate training phase was unusual, as most study protocols only feature pre‐ and post‐assessments (e.g., Bonet et al. [<reflink idref="bib13" id="ref173">13</reflink>]; Borg Sapiano et al. [<reflink idref="bib15" id="ref174">15</reflink>]; Lebdai et al. [<reflink idref="bib77" id="ref175">77</reflink>]). To verify the effectiveness of SBS in terms of students' performance and identify the impact on this relationship of SRL behaviors and self‐efficacy, we conducted a quasi‐experimental study (e.g., Min et al. [<reflink idref="bib93" id="ref176">93</reflink>]) in which we compared groups who were (experimental group) or were not (control group) exposed to SBS in their initial training, with no randomization (Cook and Campbell [<reflink idref="bib31" id="ref177">31</reflink>]) between centers or among participating students.</p> <hd id="AN0184623592-8">Study Design</hd> <p>In cooperation with nursing school managers and in line with the nursing students' course program, we conducted a multicenter quasi‐experimental study of an SBS‐based training intervention from December 2019 to March 2020 (Figure 1), ending just before the first COVID‐19 lockdown. The educational content of the SBS was adapted to the students' course program and was created and validated by a group of expert nursing tutors. This study was approved by the institutional and ethical review board of the University of (Toulouse Jean Jaures, No. IRB00011835‐2019‐11‐26‐207).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BU8/01mar25/acp70046-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="acp70046-fig-0001.jpg" title="1 Study flow chart." /> </p> <p></p> <hd id="AN0184623592-10">Groups and Participants</hd> <p></p> <hd id="AN0184623592-11">Groups</hd> <p>The study was carried out under real teaching conditions for first‐year nursing students at the beginning of the cycle. Groups were created according to the availability of SBS in the nursing schools that had this collection of SBS, and only this to ensure the same level of comparison of interface and content (read Cant and Cooper [<reflink idref="bib25" id="ref178">25</reflink>]).</p> <p>The control group was a nursing school that did not use SBS in its teaching, and therefore used "traditional" pedagogy with written support rather than SBS. The groups are not purely random. They are randomized in a natural way according to the availability of SBS collection in the nursing school and their interest in participating in a study under real classroom conditions. Handling time was planned and scheduled in their usual course in agreement with the teaching team, so it was impossible to do it at random. Only institutes wishing to participate in the experiment were randomly selected. Not all students participated.</p> <hd id="AN0184623592-12">Participants</hd> <p>Out of the 1147 first‐year nursing students recruited voluntarily from 10 nursing schools, 1183 were ultimately included and divided into two groups, and they were equivalent in terms of age, <emph>U</emph> = 128,732, <emph>p</emph> = 0.92 (Mdn = 20, SD = 7.56 for the control group; Mdn = 20, SD = 5.54 for the experimental group) and gender <emph>χ</emph><sups>2</sups> (11183), <emph>p</emph> = 0.91. The gender (male/female) ratio was 10/90 (<emph>χ</emph><sups>2</sups> = 723, <emph>p</emph> &lt; 0.001), and the mean age was 21.9 (SD = 6.1) years, a classic demographic characteristic in nursing education (Roy et al. [<reflink idref="bib125" id="ref179">125</reflink>]).</p> <p>According to Faul et al. ([<reflink idref="bib40" id="ref180">40</reflink>]) in Mendoza et al. ([<reflink idref="bib90" id="ref181">90</reflink>]), to calculate the required sample size, we used GPower for the <emph>F</emph>‐test of the two‐way analysis of variance (ANOVA). We entered the <emph>α</emph> error probability and power and the effect size as 0.05 and 0.95 and 0.4, respectively. The number of groups was two, as well as for the measurements. The output parameters indicated that the total sample size required is 64, with a critical <emph>F</emph> of 3.9. Experimental (<emph>N</emph> = 894) and control (<emph>N</emph> = 289) groups were drawn from five nursing schools per group. French nursing cohorts typically range from 100 to 250 students per year. Our sample ranged from 500 to 1250 students, as we included five nursing schools. Group size variations arose from natural differences influenced by the presence or absence of SBS in nursing schools. Ecological conditions, integrated into the program, mirrored real‐world settings, though student absences may have caused imbalances.</p> <hd id="AN0184623592-13">Environment and Types of Help</hd> <p></p> <hd id="AN0184623592-14">Experimental Group Environment</hd> <p>The SBS was accessed through a computer or tablet by logging onto the Medicactiv platform. Students entered their personal identifier and password to access the scheduled training. The SBS was a virtual 3D reproduction of a real‐life clinical care situation, allowing a nursing student to interact with a patient. Each of the three scenarios corresponded to a different clinical care situation, reflecting changes in the patient's condition (e.g., A nurse student takes care of a patient at home for knee pain caused by a road accident, then follows the patient during a rehabilitation stay and finally during a nursing consultation). The educational goal of these scenarios was to develop the ability to analyze a care situation and to ask targeted questions to gather comprehensive data, facilitating a diagnosis through clinical reasoning. These objectives align with the first competency outlined in the French nursing education framework. Students interacted with the virtual patient by clicking on the questions they wanted to ask. The interactions were displayed on the screen and made audible using recorded actors' voices to facilitate immersion and promote the acquisition of clinical reasoning through the detection of clinical signs (Figure 2) (see Mayer et al. [<reflink idref="bib88" id="ref182">88</reflink>]). Participants wore headphones to avoid disturbing the other students.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BU8/01mar25/acp70046-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="acp70046-fig-0002.jpg" title="2 Presentation of SBS for the experimental group and the interface for the control group." /> </p> <p></p> <hd id="AN0184623592-16">Control Group Environment</hd> <p>To facilitate the participation of a large control group, we transferred all the content of the SBS to the Qualtrics (Qualtrics, Provo, UT) online questionnaire platform, which allowed us to track each student's learning behaviors thanks to panel list sending. Each student was sent a login by the platform, to avoid duplication and facilitate individual coding (each click on an answer was recorded for subsequent coding). Each question corresponded to a specific scenario. In this way, the three scenarios were clearly delineated and there was no possible confusion between the answers. All audible conversations, written educational content, and knowledge questions were transposed into a single medium, namely narrative text (Chi and Wylie [<reflink idref="bib28" id="ref183">28</reflink>]). In line with Amadieu and Salmerón ([<reflink idref="bib4" id="ref184">4</reflink>]), in order to facilitate reading and understanding, we built a continuous sequence of exchanges by associating the tone of the speeches to facilitate understanding. This architecture was intended to make it easier for control participants to build a representation of the situation and better understand the task to be carried out thereafter. They answered the same questions as the experimental group. The sequence of the steps was the same as for the experimental group, and the knowledge questions were formulated and presented in the same way. By contrast, all the scenes were described verbally, without any pictures (Figure 2). To ensure the internal validity of the educational content and to facilitate a comparative analysis of the interface's effectiveness, the entire content of the SBS (developed by a team of nursing educators in a nursing school and based on the nursing skills framework) was extracted. All text, dialogues, and questions were systematically modeled in the order of appearance as in the original SBS. This recreated content was then validated by an additional team of educational trainers. Thus, the dialogue content and question hierarchization of the SBS were converted to Qualtrics for simpler, safer, and more environmentally friendly distribution.</p> <hd id="AN0184623592-17">Procedure</hd> <p>The SBS contained three scenarios that followed a patient's progression through the care process. In each scenario, students performed a clinical examination and interacted with the patient. They also had to answer questions (single choice, multiple choice or priority actions) testing their knowledge of clinical reasoning. Participants in the control group performed an educational task featuring the same three scenarios in a single medium. Each scenario was linear, and the steps followed the chronological order of care. Students in both groups had to perform these steps in the order imposed by the scenario. They were not allowed to skip a step or choose which step to start with. In both groups, each scenario lasted approximately 15–20 min.</p> <p>The procedure was divided into three parts: the initial phase, the optional training phase, and the final phase (see Appendix A1). Both the initial and final phases were conducted in the same way, consisting of reading the briefing for the first scenario of the clinical situation, self‐assessing the self‐efficacy against the success of the scenario, performing the first scenario, and finally self‐assessing the confidence judgment before reading the answers. Then, students moved on to the second and third scenarios, repeating these steps (for self‐efficacy and confidence judgment) for each scenario. The initial phase took place in an ecological context (in a classroom at each nursing school), with students providing their own computers and headphones, while the final phase was conducted remotely (home office).</p> <p>The second phase of the procedure was the training period. Students in the experimental group were given optional and unlimited access to SBS for 7 days. They could train remotely (home office) whenever they wished. Students were aware that the training scenarios were identical to those of the initial and final phase test with the same access to help, but did not include the SEP and JC self‐assessments. The same protocol applied to the traditional task performed by participants in the control group.</p> <p>The initial and final phase each lasted 60–90 min. All students were given instructions by the e‐mail panel to access the SBS or the questionnaire for the control group using their personal login. On the day of the initial phase, the experimenters checked that the students knew how to navigate the SBS, consult the answers and aids, and when to complete the questionnaires. In the case of the control group, the experimenters explained the procedure in person for the initial phase, and the necessary information was given in the online questionnaire for the initial phase and final phase.</p> <hd id="AN0184623592-18">Description of Help Seeking</hd> <p>To assess the requests for help from students in the <emph>experimental group</emph>, we requested a special development from the editor (SimforHealth) that would enable us to extract the digital traces of SBS use. At the end of each scenario, students could obtain feedback on their answers if they so wished. To avoid the immersive withdrawal of students from the scenario, we opted for reading the answers at the end of the scenario and not during. Because the feedback included hyperlinks and documents on the theme of care, the return to immersion would have been difficult. Consulting feedback is regarded as the key mechanism behind SRL behavior (Butler and Winne [<reflink idref="bib23" id="ref185">23</reflink>]) but although help was available, it was not necessarily used (Burgues et al. [<reflink idref="bib20" id="ref186">20</reflink>]). Answers were color‐coded: green for a correct answer and red for an incorrect one. Students had the option of requesting additional help to explain the feedback. Based on Nelson‐Le Gall ([<reflink idref="bib100" id="ref187">100</reflink>])'s theory, we established student profiles only according to the type of help they actually consulted, according to the digital traces (Hakimi et al. [<reflink idref="bib51" id="ref188">51</reflink>]; Lavoué et al. [<reflink idref="bib76" id="ref189">76</reflink>]; Regan and Jesse [<reflink idref="bib118" id="ref190">118</reflink>]) (Figure 3).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BU8/01mar25/acp70046-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="acp70046-fig-0003.jpg" title="3 Help‐seeking presentation for experimental and control groups." /> </p> <p></p> <p>To assess the <emph>control group</emph>'s requests for help, we included specific questions at the end of each scenario. Students were given the opportunity to consult their feedback by clicking on "Yes" in response to the question "Would you like to consult your feedback?" If they answered "Yes," another question appeared after the feedback: "Would you like to consult an explanation (i.e., help) of the feedback?" If the answer was "Yes," a window opened with the requested help. If the answer was "No," students were given the next question (Figure 3).</p> <p>To our knowledge, very few studies in nursing sciences have used digital trace data to understand student behavior. In the present study, we analyzed digital trace data to explore students' SRL strategies and performance.</p> <hd id="AN0184623592-20">Variables Measured for Both Groups</hd> <p></p> <hd id="AN0184623592-21">Help‐Seeking Measure</hd> <p>At the end of each scenario, students in the <emph>experimental group</emph> could either consult their feedback or skip this step by clicking on "Next." In accordance with Nelson‐Le Gall ([<reflink idref="bib100" id="ref191">100</reflink>])'s theory, we were able to define three student profiles based on their level of SRL behavior. More specifically, we analyzed digital trace data to find out which students consulted the feedback and any additional help (Hakimi et al. [<reflink idref="bib51" id="ref192">51</reflink>]; Lavoué et al. [<reflink idref="bib76" id="ref193">76</reflink>]; Regan and Jesse [<reflink idref="bib118" id="ref194">118</reflink>]). Students who did not consult the feedback were classified as <emph>help avoidant</emph>. Those who only consulted the feedback were classified as <emph>executive help seekers</emph>. Students who consulted both the feedback and additional help were classified as <emph>instrumental help seekers</emph>.</p> <p>Again in accordance with Nelson‐Le Gall ([<reflink idref="bib100" id="ref195">100</reflink>])'s theory, we were able to define three student profiles for the <emph>control group</emph>, based on their SRL behavior. If students replied "No" to the question "Would you like to consult your feedback?", they were classified as help avoidant, and were given the next question. If they replied "Yes" and actually consulted their feedback, they were classified as executive help seekers. If students clicked "Yes" again, when asked "Would you like to consult an explanation of the feedback?", they were classified as instrumental help seekers. If, however, they clicked on "No," they were classified as executive help seekers.</p> <hd id="AN0184623592-22">Performance Measure</hd> <p>Students were asked to respond to questions during the three scenarios. A total score (out of 100) was obtained by summing the correct answers (each scored 2) to the 50 questions (e.g., Gu et al. [<reflink idref="bib48" id="ref196">48</reflink>]; Koivisto et al. [<reflink idref="bib72" id="ref197">72</reflink>]; Liou et al. [<reflink idref="bib80" id="ref198">80</reflink>]; Olaussen et al. [<reflink idref="bib103" id="ref199">103</reflink>]). Students with a total score &gt; 60 were deemed to have performed well. The reliability analysis of the results by Cronbach's <emph>α</emph> was 0.799.</p> <hd id="AN0184623592-23">Self‐Efficacy Measure</hd> <p>Students were asked to rate their self‐efficacy before beginning each of the three scenarios and after reading the contextual briefing on a numerical scale ranging from 0 (<emph>Not at all capable</emph>) to 100 (<emph>Absolutely capable</emph>) (see Bandura [<reflink idref="bib7" id="ref200">7</reflink>], [<reflink idref="bib9" id="ref201">9</reflink>]). Self‐efficacy was assessed twice: in the initial and final phases. Cronbach's <emph>α</emph> was 0.909.</p> <hd id="AN0184623592-24">Confidence Judgment Measure</hd> <p>At the end of each scenario, but before the feedback was available, each student answered the question "How accurate do you feel you were in answering these questions?" on a numerical scale ranging from 0 (<emph>Not at all accurate</emph>) to 100 (<emph>Completely accurate</emph>). The accuracy of this self‐assessment was calculated by subtracting the actual performance from the estimated one (Baars et al. [<reflink idref="bib6" id="ref202">6</reflink>]; Gonida and Leondari [<reflink idref="bib46" id="ref203">46</reflink>]; Schraw [<reflink idref="bib129" id="ref204">129</reflink>]). For example, if a student estimated their performance as 70/100, whereas their actual performance was 90/100, it would be an underestimate, because the difference would be negative (70 − 90 = −20). Conversely, if the estimated performance was 80/100 and the actual performance was 70/100, then it would be an overestimate, as the difference would be positive (80 − 70 = 10).</p> <p>We then calculated the amplitude of the estimation bias as the difference between the absolute values of these estimations. For example, if a student provided an underestimate (−20) and then an overestimate (+10), the absolute values would be 20 and 10, and the difference between the two would be 10 (20 − 10 = 10). The closer the value is to 0, the more accurate the student's self‐assessment (Gonida and Leondari [<reflink idref="bib46" id="ref205">46</reflink>]). The reliability analysis of the results by Cronbach's <emph>α</emph> was 0.707.</p> <hd id="AN0184623592-25">Data Preparation</hd> <p>Data were expressed in numbers and percentages for categorical variables and means (±SD) for quantitative variables. Analyses of variance (ANOVAs) with two or three factors were performed to compare groups and SRL profiles on repeated measures (timepoint, performance, self‐efficacy, absolute value of difference between estimated and actual performances). The significance threshold was set at <emph>p</emph> &lt; 0.05. Paired <emph>t</emph> tests were performed to compare significant interactions. Before each test‐<emph>t</emph>, the Shapiro‐Wilk and Levene's tests were carried out to guide us on the use of the parametric or non‐parametric test. In case of violation of normality, the non‐parametric Mann–Whitney test (<emph>U</emph>) was used. Spearman's rho (<emph>ρ</emph>) was calculated to assess the correlations between self‐efficacy and self‐regulated profiles and validate (or not) the consistency hypothesis (all <emph>p</emph>s &lt; 0.001, Bonferroni corrected). The mediation of confidence judgment as a mediating factor of performance was analyzed with hierarchical regression and model comparison analysis (Δ<emph>R</emph><sups>2</sups>) (Rascle and Irachabal [<reflink idref="bib117" id="ref206">117</reflink>]). Statistics were computed using (Jamovi [<reflink idref="bib59" id="ref207">59</reflink>], s.d. Version 2.3.0).</p> <hd id="AN0184623592-26">Results</hd> <p></p> <hd id="AN0184623592-27">Performance, Group, and Timepoint</hd> <p>A mixed ANOVA with timepoint as a repeated measure and group as the independent variable revealed no significant main effect of timepoint, <emph>F</emph>(<reflink idref="bib1" id="ref208">1</reflink>, 864) = 0.218, <emph>p</emph> = 0.64, but a significant main effect of group, <emph>F</emph>(<reflink idref="bib1" id="ref209">1</reflink>, 864) = 384, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.308, and an interaction effect, <emph>F</emph>(<reflink idref="bib1" id="ref210">1</reflink>, 864) = 442.92, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.339. The effect of timepoint on performance depended on the group. Unexpectedly, Bonferroni's test results revealed that the control group performed more poorly in the final phase than in the initial phase, <emph>t</emph>(<reflink idref="bib864" id="ref211">864</reflink>) = 11.73, <emph>p</emph> &lt; 0.001, whereas the experimental group performed significantly better in the final phase than in the initial phase, <emph>t</emph>(<reflink idref="bib864" id="ref212">864</reflink>) = −22.3, <emph>p</emph> &lt; 0.001 (Table 1).</p> <p>1 TABLE Mean performances according to help‐seeking behavior and group.</p> <p> <ephtml> &lt;table&gt;&lt;thead valign="bottom"&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="center"&gt;Experimental&lt;/th&gt;&lt;th align="center"&gt;Control&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="center"&gt;Initial phase, &lt;italic&gt;M&lt;/italic&gt; (SD)&lt;/th&gt;&lt;th align="center"&gt;Final phase, &lt;italic&gt;M&lt;/italic&gt; (SD)&lt;/th&gt;&lt;th align="center"&gt;Initial phase, &lt;italic&gt;M&lt;/italic&gt; (SD)&lt;/th&gt;&lt;th align="center"&gt;Final phase, &lt;italic&gt;M&lt;/italic&gt; (SD)&lt;/th&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody valign="top"&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;666&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;200&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Performance&lt;/td&gt;&lt;td align="center"&gt;54.1 (13.2)&lt;/td&gt;&lt;td align="center"&gt;63.6 (11.9)&lt;/td&gt;&lt;td align="center"&gt;43.7 (18.1)&lt;/td&gt;&lt;td align="center"&gt;34.6 (15.3)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;805&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;200&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;SE&lt;/td&gt;&lt;td align="center"&gt;56.8 (17.6)&lt;/td&gt;&lt;td align="center"&gt;61.6 (15.9)&lt;/td&gt;&lt;td align="center"&gt;49.6 (18.2)&lt;/td&gt;&lt;td align="center"&gt;46.5 (17.8)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;JC&lt;/td&gt;&lt;td align="center"&gt;61.8 (16.4)&lt;/td&gt;&lt;td align="center"&gt;71 (13.6)&lt;/td&gt;&lt;td align="center"&gt;52.6 (18.1)&lt;/td&gt;&lt;td align="center"&gt;46.7 (22.5)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;JC accuracy&lt;/td&gt;&lt;td align="center"&gt;9.27 (10.4)&lt;/td&gt;&lt;td align="center"&gt;8.78 (10.7)&lt;/td&gt;&lt;td align="center"&gt;12 (10.2)&lt;/td&gt;&lt;td align="center"&gt;10.7 (10.4)&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <p>1 Abbreviations: JC = confidence judgment; SE = self‐efficacy.</p> <hd id="AN0184623592-28">Self‐Efficacy, Group, and Timepoint</hd> <p>A mixed ANOVA with self‐efficacy as the repeated measure and group as the independent variable revealed significant effects of timepoint, <emph>F</emph>(<reflink idref="bib1" id="ref213">1</reflink>, 1003) = 4.69, <emph>p</emph> = 0.031, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.005, group, <emph>F</emph>(<reflink idref="bib1" id="ref214">1</reflink>, 1003) = 75.1, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.070, and the Timepoint * Group interaction, <emph>F</emph>(<reflink idref="bib1" id="ref215">1</reflink>, 1003) = 103.57, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.094, on performance. Follow‐up <emph>Bonferroni t</emph>‐tests showed that self‐efficacy was lower in the final phase than in the initial phase for the control group, <emph>t</emph>(<reflink idref="bib199" id="ref216">199</reflink>) = 4.65, <emph>p</emph> = 1, Cohen's <emph>d</emph> = 0.329, whereas it was significantly higher in the final phase than in the initial phase one for the experimental group, <emph>t</emph>(<reflink idref="bib804" id="ref217">804</reflink>) = 13.7, <emph>p</emph> &lt; 0.001, Cohen's <emph>d</emph> = 0.483.</p> <hd id="AN0184623592-29">Performance According to Type of Help Used and Timepoint</hd> <p>We calculated a mixed three‐factor ANOVA with timepoint as the repeated measure, group and SRL profile (avoidance, executive, instrumental) as the independent measures, and performance as the dependent variable. Results revealed significant effects of timepoint, <emph>F</emph>(<reflink idref="bib1" id="ref218">1</reflink>, 860) = 5.84, <emph>p</emph> = 0.016, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.007, and group, <emph>F</emph>(<reflink idref="bib1" id="ref219">1</reflink>, 860) = 272.11, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.240, but not of profile, <emph>F</emph>(<reflink idref="bib2" id="ref220">2</reflink>, 860) = 2.75, <emph>p</emph> = 0.064, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.006, on performance. There were significant interactions between timepoint and group, <emph>F</emph>(<reflink idref="bib1" id="ref221">1</reflink>, 860) = 305.32, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.262, timepoint and profile, <emph>F</emph>(<reflink idref="bib2" id="ref222">2</reflink>, 860) = 9.39, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.021, and group and profile, <emph>F</emph>(<reflink idref="bib2" id="ref223">2</reflink>, 860) = 5.5, <emph>p</emph> = 0.004, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.013, but not between timepoint, group, and profile, <emph>F</emph>(<reflink idref="bib2" id="ref224">2</reflink>, 860) = 2.21, <emph>p</emph> = 0.11, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.005. Subsequent <emph>t</emph>‐tests showed that participants in the experimental group who used instrumental help (<emph>n</emph> = 31) performed significantly better in the final phase (<emph>M</emph> = 73.3, SD = 7.09) than in the initial phase (<emph>M</emph> = 58.1, SD = 14.07), <emph>t</emph>(<reflink idref="bib30" id="ref225">30</reflink>) = 6.5, <emph>p</emph> &lt; 0.001, Cohen's <emph>d</emph> = 1.17, as did those who used executive help (<emph>n</emph> = 354; <emph>M</emph> = 64.6, SD = 11.7 vs. <emph>M</emph> = 57.2, SD = 12.9), <emph>t</emph>(<reflink idref="bib353" id="ref226">353</reflink>) = 13, <emph>p</emph> &lt; 0.001, Cohen's <emph>d</emph> = 0.691, and those who avoided help (<emph>n</emph> = 281, <emph>M</emph> = 61.2, SD = 11.8 vs. <emph>M</emph> = 49.8, SD = 12.1), <emph>t</emph>(<reflink idref="bib280" id="ref227">280</reflink>) = 21.2, <emph>p</emph> &lt; 0.001, Cohen's <emph>d</emph> = 1.26 (Table 2).</p> <p>2 TABLE Self‐estimated accuracy of performance according to group and timepoint.</p> <p> <ephtml> &lt;table&gt;&lt;thead valign="bottom"&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="center"&gt;Performance&lt;/th&gt;&lt;th align="center"&gt;SE&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="center"&gt;Experimental group (&lt;italic&gt;N&lt;/italic&gt;&amp;#8201;=&amp;#8201;666)&lt;xref ref-type="fn" rid="tfn3" /&gt;&lt;/th&gt;&lt;th align="center"&gt;Control group (&lt;italic&gt;N&lt;/italic&gt;&amp;#8201;=&amp;#8201;200)&lt;xref ref-type="fn" rid="tfn3" /&gt;&lt;/th&gt;&lt;th align="center"&gt;Experimental group (&lt;italic&gt;N&lt;/italic&gt;&amp;#8201;=&amp;#8201;666)&lt;/th&gt;&lt;th align="center"&gt;Control group (&lt;italic&gt;N&lt;/italic&gt;&amp;#8201;=&amp;#8201;200)&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th align="left"&gt;Help&amp;#8208;seeking&lt;/th&gt;&lt;th align="center"&gt;&lt;italic&gt;M&lt;/italic&gt;&lt;/th&gt;&lt;th align="center"&gt;95% CI&lt;/th&gt;&lt;th align="center"&gt;&lt;italic&gt;M&lt;/italic&gt;&lt;/th&gt;&lt;th align="center"&gt;95% CI&lt;/th&gt;&lt;th align="center"&gt;&lt;italic&gt;M&lt;/italic&gt;&lt;/th&gt;&lt;th align="center"&gt;95% CI&lt;/th&gt;&lt;th align="center"&gt;&lt;italic&gt;M&lt;/italic&gt;&lt;/th&gt;&lt;th align="center"&gt;95% CI&lt;/th&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody valign="top"&gt;&lt;tr&gt;&lt;td align="left"&gt;Avoidance help&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;281&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;25&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;281&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;25&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Initial phase&lt;/td&gt;&lt;td align="center"&gt;49.8&lt;/td&gt;&lt;td align="center"&gt;[48.1&amp;#8211;51.4]&lt;/td&gt;&lt;td align="center"&gt;43.7&lt;/td&gt;&lt;td align="center"&gt;[38.2&amp;#8211;49.2]&lt;/td&gt;&lt;td align="center"&gt;56.9&lt;/td&gt;&lt;td align="center"&gt;[54.8&amp;#8211;58.9]&lt;/td&gt;&lt;td align="center"&gt;45.6&lt;/td&gt;&lt;td align="center"&gt;[38.7&amp;#8211;52.5]&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Final phase&lt;/td&gt;&lt;td align="center"&gt;61.2&lt;/td&gt;&lt;td align="center"&gt;[59.7&amp;#8211;62.7]&lt;/td&gt;&lt;td align="center"&gt;36.2&lt;/td&gt;&lt;td align="center"&gt;[31.4&amp;#8211;41.1]&lt;/td&gt;&lt;td align="center"&gt;65.3&lt;/td&gt;&lt;td align="center"&gt;[63.4&amp;#8211;67.3]&lt;/td&gt;&lt;td align="center"&gt;39.7&lt;/td&gt;&lt;td align="center"&gt;[33.1&amp;#8211;46.2]&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Executive help&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;354&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;97&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;354&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;97&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Initial phase&lt;/td&gt;&lt;td align="center"&gt;57.4&lt;/td&gt;&lt;td align="center"&gt;[56&amp;#8211;58.9]&lt;/td&gt;&lt;td align="center"&gt;45.2&lt;/td&gt;&lt;td align="center"&gt;[42.4&amp;#8211;48]&lt;/td&gt;&lt;td align="center"&gt;58&lt;/td&gt;&lt;td align="center"&gt;[56.1&amp;#8211;59.8]&lt;/td&gt;&lt;td align="center"&gt;49.5&lt;/td&gt;&lt;td align="center"&gt;[46&amp;#8211;53]&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Final phase&lt;/td&gt;&lt;td align="center"&gt;64.9&lt;/td&gt;&lt;td align="center"&gt;[63.6&amp;#8211;66.2]&lt;/td&gt;&lt;td align="center"&gt;34.8&lt;/td&gt;&lt;td align="center"&gt;[32.3&amp;#8211;37.3]&lt;/td&gt;&lt;td align="center"&gt;68.4&lt;/td&gt;&lt;td align="center"&gt;[66.7&amp;#8211;70.2]&lt;/td&gt;&lt;td align="center"&gt;42.9&lt;/td&gt;&lt;td align="center"&gt;[39.6&amp;#8211;46.3]&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Instrumental help&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;31&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;78&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;31&lt;/td&gt;&lt;td align="center"&gt;n&amp;#8201;=&amp;#8201;78&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Initial phase&lt;/td&gt;&lt;td align="center"&gt;58.1&lt;/td&gt;&lt;td align="center"&gt;[53.1&amp;#8211;63]&lt;/td&gt;&lt;td align="center"&gt;42.1&lt;/td&gt;&lt;td align="center"&gt;[39&amp;#8211;45.3]&lt;/td&gt;&lt;td align="center"&gt;65.6&lt;/td&gt;&lt;td align="center"&gt;[59.4&amp;#8211;71.8]&lt;/td&gt;&lt;td align="center"&gt;50.9&lt;/td&gt;&lt;td align="center"&gt;[47&amp;#8211;54.8]&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Final phase&lt;/td&gt;&lt;td align="center"&gt;73.3&lt;/td&gt;&lt;td align="center"&gt;[68.9&amp;#8211;77]&lt;/td&gt;&lt;td align="center"&gt;34.1&lt;/td&gt;&lt;td align="center"&gt;[31.4&amp;#8211;36.9]&lt;/td&gt;&lt;td align="center"&gt;76&lt;/td&gt;&lt;td align="center"&gt;[70.2&amp;#8211;81.9]&lt;/td&gt;&lt;td align="center"&gt;45.1&lt;/td&gt;&lt;td align="center"&gt;[41.5&amp;#8211;48.8]&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <ulist> <item>2 Abbreviations: CI = confidence interval; SE = self‐efficacy.</item> <item>3 * Number of participants retained by the set by the statistical software Jamovi (version 2.3.0) for the analysis of variance.</item> </ulist> <p>For the control group, results showed that participants who used instrumental help (<emph>n</emph> = 78) did not perform significantly better in the final phase (<emph>M</emph> = 34.1, SD = 15.9) than in the initial phase (<emph>M</emph> = 42.1, SD = 18.8), <emph>t</emph>(<reflink idref="bib77" id="ref228">77</reflink>) = 6.21, <emph>p</emph> &lt; 0.001, Cohen's <emph>d</emph> = 0.703. A Wilcoxon signed‐rank test revealed that participants (<emph>n</emph> = 97) who used executive help did not perform significantly better in the final phase (<emph>M</emph> = 34.5, SD = 15) than in the initial phase (<emph>M</emph> = 44.9, SD = 17.4), <emph>t</emph>(<reflink idref="bib96" id="ref229">96</reflink>) = 7.42, <emph>p</emph> = 1, Cohen's <emph>d</emph> = 0.754. A <emph>t</emph>‐test revealed that the same was true for participants (<emph>n</emph> = 25) who avoided help (<emph>M</emph> = 36.2, SD = 15.1 vs. <emph>M</emph> = 43.7, SD = 18.4), <emph>t</emph>(<reflink idref="bib24" id="ref230">24</reflink>) = 3.71, <emph>p</emph> = 0.99, Cohen's <emph>d</emph> = 0.743.</p> <hd id="AN0184623592-30">Self‐Efficacy and Help Use (SRL Profile)</hd> <p>There was a significant negative correlation between self‐efficacy and SRL profile (<emph>ρ</emph> = −0.082, <emph>p</emph> = 0.016), indicating that our results tended to confirm the consistency hypothesis. Participants with high self‐efficacy perceived themselves to be very competent and less in need of seeking help, as this behavior would not have been consistent with their perception. Nevertheless, the value of the correlation was close to zero (Table 3).</p> <p>3 TABLE Correlations between profiles, self‐efficacy, and timepoint.</p> <p> <ephtml> &lt;table&gt;&lt;thead valign="bottom"&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="center" /&gt;&lt;th align="center"&gt;Self&amp;#8208;regulated profiles&lt;/th&gt;&lt;th align="center"&gt;Initial phase SE&lt;/th&gt;&lt;th align="center"&gt;Final phase SE&lt;/th&gt;&lt;th align="center"&gt;Initial phase performance&lt;/th&gt;&lt;th align="center"&gt;Final phase performance&lt;/th&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody valign="top"&gt;&lt;tr&gt;&lt;td align="left"&gt;Self&amp;#8208;regulated profiles&lt;/td&gt;&lt;td align="center"&gt;Spearman's &amp;#961;&lt;/td&gt;&lt;td align="center"&gt;&amp;#8212;&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;p&lt;/td&gt;&lt;td align="center"&gt;&amp;#8212;&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Initial phase SE&lt;/td&gt;&lt;td align="center"&gt;Spearman's &amp;#961;&lt;/td&gt;&lt;td align="center"&gt;&amp;#8722;0.064*&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;p&lt;/td&gt;&lt;td align="center"&gt;0.049&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Final phase SE&lt;/td&gt;&lt;td align="center"&gt;Spearman's &amp;#961;&lt;/td&gt;&lt;td align="center"&gt;0.082*&lt;/td&gt;&lt;td align="center"&gt;0.830***&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;p&lt;/td&gt;&lt;td align="center"&gt;0.016&lt;/td&gt;&lt;td align="center"&gt;&amp;#60;&amp;#8201;0.001&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Initial phase performance&lt;/td&gt;&lt;td align="center"&gt;Spearman's &amp;#961;&lt;/td&gt;&lt;td align="center"&gt;0.054&lt;/td&gt;&lt;td align="center"&gt;0.105***&lt;/td&gt;&lt;td align="center"&gt;0.186***&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;p&lt;/td&gt;&lt;td align="center"&gt;0.096&lt;/td&gt;&lt;td align="center"&gt;&amp;#60;&amp;#8201;0.001&lt;/td&gt;&lt;td align="center"&gt;&amp;#60;&amp;#8201;0.001&lt;/td&gt;&lt;td align="center" /&gt;&lt;td align="center" /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Final phase performance&lt;/td&gt;&lt;td align="center"&gt;Spearman's &amp;#961;&lt;/td&gt;&lt;td align="center"&gt;&amp;#8722;0.109**&lt;/td&gt;&lt;td align="center"&gt;0.111**&lt;/td&gt;&lt;td align="center"&gt;0.308***&lt;/td&gt;&lt;td align="center"&gt;0.631***&lt;/td&gt;&lt;td align="center"&gt;&amp;#8212;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;p&lt;/td&gt;&lt;td align="center"&gt;0.001&lt;/td&gt;&lt;td align="center"&gt;0.001&lt;/td&gt;&lt;td align="center"&gt;&amp;#60;&amp;#8201;0.001&lt;/td&gt;&lt;td align="center"&gt;&amp;#60;&amp;#8201;0.001&lt;/td&gt;&lt;td align="center"&gt;&amp;#8212;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <ulist> <item>4 <emph>Note:</emph> *<emph>p</emph> &lt; 0.05, **<emph>p</emph> &lt; 0.01, ***<emph>p</emph> &lt; 0.001.</item> <item>5 Abbreviation: SE = self‐efficacy.</item> </ulist> <p>A three‐factor ANOVA was performed with timepoint as the repeated measure, group and SRL profile as independent measures, and self‐efficacy as the dependent variable. Results revealed significant effects of timepoint, <emph>F</emph>(<reflink idref="bib1" id="ref231">1</reflink>, 860) = 8.58, <emph>p</emph> = 0.003, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.01, and group, <emph>F</emph>(<reflink idref="bib1" id="ref232">1</reflink>, 860) = 48.06, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.053, on self‐efficacy, and a nonsignificant effect of profile, <emph>F</emph>(<reflink idref="bib2" id="ref233">2</reflink>, 860) = 0.76, <emph>p</emph> = 0.46, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.002.</p> <p>There was a significant effect of the Timepoint * Group interaction, <emph>F</emph>(<reflink idref="bib1" id="ref234">1</reflink>, 860) = 66.038, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.071, but no significant effects of the interactions between timepoint and profile, <emph>F</emph>(<reflink idref="bib2" id="ref235">2</reflink>, 860) = 0.46, <emph>p</emph> = 0.631, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.001, group and profile, <emph>F</emph>(<reflink idref="bib2" id="ref236">2</reflink>, 860) = 0.494, <emph>p</emph> = 0.61, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.001, or timepoint, group and profile, <emph>F</emph>(<reflink idref="bib2" id="ref237">2</reflink>, 860) = 1.942, <emph>p</emph> = 0.144, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.004 (Figure 4). These results indicated that self‐efficacy may contribute to different help‐seeking behaviors and to self‐regulation in general (Moos and Azevedo [<reflink idref="bib94" id="ref238">94</reflink>]).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BU8/01mar25/acp70046-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="acp70046-fig-0004.jpg" title="4 Distribution of profiles according to performance and timepoint." /> </p> <p></p> <hd id="AN0184623592-32">Confidence Judgment and Accuracy</hd> <p>The mixed ANOVA revealed significant effects of timepoint, <emph>F</emph>(<reflink idref="bib1" id="ref239">1</reflink>, 864) = 6.18, <emph>p</emph> = 0.013, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.007, and group, <emph>F</emph>(<reflink idref="bib1" id="ref240">1</reflink>, 864) = 11.8, <emph>p</emph> &lt; 0.001, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.013, on confidence judgments. Students in the experimental group produced higher confidence judgments than those in the control group. The effect of the Timepoint * Group interaction on the absolute value of confidence judgment was not significant, <emph>F</emph>(<reflink idref="bib1" id="ref241">1</reflink>, 864) = 1.07, <emph>p</emph> = 0.30, <emph>η</emph><subs><emph>p</emph></subs><sups>2</sups> = 0.01. When confidence judgment is added to the linear regression model in the second step, a significant increase in explained variance is observed, Δ<emph>R</emph><sups>2</sups> = 0.0118, <emph>F</emph>(<reflink idref="bib1" id="ref242">1</reflink>, 863) = 789, <emph>p</emph> &lt; 0.001. Additionally, the decrease in AIC (from 6959 to 6841) indicates an overall improvement in model quality. With this addition, the adjusted <emph>R</emph><sups>2</sups> increases from 0.478 to 0.488. These results suggest that confidence judgment acts as a mediator in the relationship between the studied variables and performance.</p> <p>The experimental group was more accurate than the control group at both time points. Table 2 summarizes the mean absolute values of the differences between estimated and actual performances for the two groups in the pre‐ and final phases.</p> <hd id="AN0184623592-33">Discussion</hd> <p>Despite the growing use of SBS in initial training, which accelerated during the COVID‐19 pandemic, it has so far been poorly assessed (Decormeille et al. [<reflink idref="bib35" id="ref243">35</reflink>]; Sim et al. [<reflink idref="bib138" id="ref244">138</reflink>]). To facilitate its use and identify the advantages of this educational innovation, it is necessary to study how students learn with SBS. Few studies have so far investigated the actual learning behavior of healthcare students with SBS in terms of self‐regulation theory. As highlighted by Sim et al.'s meta‐analysis (2022), only one study in France is referenced on this topic (see Blanié, Rihane, et al. [<reflink idref="bib12" id="ref245">12</reflink>]). The authors focused on assessing theoretical knowledge before and after the intervention, as well as satisfaction, motivation, and self‐assessment of clinical reasoning among 146 s‐year students. However, they did not explore the students' learning behaviors. Furthermore, the inclusion of students was conducted under laboratory conditions, without explaining the study's objectives to them.</p> <p>The present study, conducted under ecological conditions, was designed to test the effectiveness of SBS (multimedia) on learning clinical reasoning by comparing it with traditional education (single medium) on self‐efficacy beliefs, self‐regulation strategy, confidence judgments, and performance.</p> <hd id="AN0184623592-34">Impact of SBS on Performance</hd> <p>As expected, and in line with previous studies (e.g., Blanié, Amorim, et al. [<reflink idref="bib11" id="ref246">11</reflink>]), the experimental group performed significantly better than the control group, and better in the final phase than in the initial phase. By contrast, the control group performed more poorly in the final phase than the initial phase. In the control condition, the use of a single medium potentially overloaded the visual channel, whereas in the experimental group, the cognitive load was distributed between the auditory and visual channels, according to Mayer's theory (Mayer [<reflink idref="bib87" id="ref247">87</reflink>]). Indeed, to meet the criteria of rigor of SBS creation (read Koivisto et al. [<reflink idref="bib70" id="ref248">70</reflink>]), there are recorded actors' voices to increase immersion and detection of clinical signs that make it easier to acquire clinical reasoning to construct a nursing clinical judgment. This auditory channel, associated with the reading of verbal exchanges and a significant 3D graphic level produced by 3D artists under Unity, makes these conditions seem to facilitate the acquisition of knowledge. In accordance with Mayer's theory (2014), the multiplicity of sensory channels to disseminate information facilitates the acquisition and long‐term memory retention compared to a single medium. Thus, SBS was more efficient than traditional education. The difference in performance impacted self‐efficacy ratings.</p> <hd id="AN0184623592-35">SBS and Self‐Efficacy</hd> <p>Performance unexpectedly improved with self‐efficacy and experience, but only in the experimental group. Students in the experimental group benefited from a more realistic scenario, making it easier for them to identify the clinical practice. For this reason, SBS may have increased self‐efficacy. By contrast, self‐efficacy decreased with experience in the control group. This result can be explained by the fact that not only did performance decrease as experience increased, but it seemed more difficult to obtain a credible representation of the case without SBS (Mayer's theory; ADD REF). According to Bandura ([<reflink idref="bib8" id="ref249">8</reflink>]), one source of self‐efficacy is previous experience. In the control group, the decline in performance led to lower self‐efficacy in the final phase. In addition, it is more difficult for learners to develop a relevant mental model of the situation when it is only described in a text, rather than shown in images, texts, or animation, as was the case in the SBS group. These differences may explain why self‐efficacy was lower in the control group. Thus, SBS increased self‐efficacy.</p> <hd id="AN0184623592-36">SBS, Help Use, and Performance</hd> <p>Concerning self‐regulation, results unexpectedly revealed that the type of help used had no effect on performance. Several hypotheses can be put forward to explain this unexpected finding. First, processing help, especially instrumental help, is cognitively demanding. Second, help‐seeking behavior is perceived by some students as a threat to their skills, leading them to avoid using help even when it is needed (e.g., Cheong et al. [<reflink idref="bib27" id="ref250">27</reflink>]). It may also be perceived by students as a threat to their autonomy (e.g., Butler [<reflink idref="bib21" id="ref251">21</reflink>]). The high rate of help‐seeking avoidance in the experimental group (Table 2) can be explained by the realistic situation generated by the SBS, as this may have reinforced the perceived threat to skills if help was sought. According to Mayer's theory (ADD REF), the use of realistic information, both visual and auditory (recorded voices of actors), to increase immersion enhances memory retention while imposing a lower cognitive load. Although there was a lower rate of help‐seeking avoidance in the control group (Table 2) and students adopted more appropriate help‐seeking behaviors, their performance was quite poor, and their help‐seeking behavior did not change significantly between initial phases and final phases.</p> <p>In addition, the higher proportion of students who used help (instrumental and executive) in the control group can be explained by the higher cognitive load induced by the use of a single medium. As the situation was less realistic, it was more difficult to elaborate on a mental model than it was in the SBS group. More help may therefore have been needed in the control group than in the experimental one. However, another possibility is that students have already seen what feedback looks like under experimental conditions and have decided that it is not useful to them. In fact, this is one of the limitations of the platform, which does not adapt help depending on the answer given.</p> <hd id="AN0184623592-37">SBS, Self‐Efficacy, and Help Use: Consistency Hypothesis?</hd> <p>As predicted by Butler ([<reflink idref="bib21" id="ref252">21</reflink>]), students with high self‐efficacy were less likely to use help than those with low self‐efficacy, as admitting that they needed help would not have been consistent with their self‐perception, according to the consistency hypothesis. However, this result must be considered with caution, for although the correlation was significant, it was very weak (<emph>ρ</emph> = 0.08). The significance stemmed more from the large number of participants than from the actual strength of the relationship.</p> <hd id="AN0184623592-38">Confidence Judgments as a Function of Experience and Group</hd> <p>Concerning confidence judgments, results revealed that those produced by the experimental group were higher than those produced by the control group. SBS leads to more accurate retrospective judgments when students interact with an SBS after a training period than with a non‐SBS control. This result shows that SBS leads to more accurate retrospective judgments than traditional education. Confidence judgment accuracy has been shown to be important in terms of the relevance of subsequent self‐regulation (e.g., Hattie [<reflink idref="bib52" id="ref253">52</reflink>]). In metacognitive models, regulation or control depends on monitoring accuracy (e.g., Nelson and Narens [<reflink idref="bib99" id="ref254">99</reflink>]) and affects learning performance. However, it also depends on cognitive load (e.g., Van Gog et al. [<reflink idref="bib147" id="ref255">147</reflink>]). If a task is very cognitively demanding, as was the case in our experiment, especially as the students were novices, it is more likely to be associated with low judgments of confidence (Baars et al. [<reflink idref="bib6" id="ref256">6</reflink>]). The control group's lower confidence judgments can therefore be seen as an indicator of the difficulties reflected by poorer performances in the control group than in the experimental group. Considering the impact of the cognitive load induced by the learning environment on monitoring processes could therefore contribute to our understanding of learners' self‐regulation (e.g., De Bruin et al. [<reflink idref="bib19" id="ref257">19</reflink>]). As previously mentioned, the level of SRL depends on multiple factors, including cognitive load. According to Seufert ([<reflink idref="bib136" id="ref258">136</reflink>]), cognitive load can influence self‐regulation, and vice versa.</p> <p>Van Gog et al. ([<reflink idref="bib147" id="ref259">147</reflink>]) reminded us that cognitive load can depend on the complexity of the task to be performed. In the present study, the traditional education condition generated a heavier cognitive load, owing to the use of a single medium (visual channel; see Mayer's theory; ADD REF), and probably affected the performance of controls. According to Paas et al. ([<reflink idref="bib105" id="ref260">105</reflink>]), SRL is often ineffectual, especially for novices such as those in our study, but our results showed that learning with SBS favors retrospective monitoring accuracy, self‐regulation, and performance.</p> <p>From the perspective of improving monitoring accuracy and self‐regulation, SBS systems should record the accuracy of confidence judgments and provide feedback, so that students can use it to improve their subsequent self‐assessments (i.e., Kostons et al. [<reflink idref="bib75" id="ref261">75</reflink>]).</p> <p>Finally, as with other studies that focus on learning through SBS, this study primarily examines students' theoretical knowledge. There is a notable lack of research on self‐regulation learning, particularly under real conditions. The present study aimed to fill this gap. To enhance the experience of SBS in initial training, it is beneficial for students to receive feedback on their responses to support self‐assessment and facilitate knowledge acquisition. Whenever possible, students should be encouraged to evaluate their own sense of self‐efficacy beliefs, as this is a crucial determinant of performance (Bandura [<reflink idref="bib7" id="ref262">7</reflink>]; MacLean et al. [<reflink idref="bib83" id="ref263">83</reflink>]; Merino‐Soto et al. [<reflink idref="bib92" id="ref264">92</reflink>]; Yiin et al. [<reflink idref="bib160" id="ref265">160</reflink>]) and to assess their confidence in their abilities (Baars et al. [<reflink idref="bib6" id="ref266">6</reflink>]). While SBS can be utilized either synchronously or asynchronously, it is important that students receive a debriefing from the instructor at the end of the scenario, based on the established educational objectives (Cant and Cooper [<reflink idref="bib25" id="ref267">25</reflink>]). Moreover, relying solely on this technology does not ensure optimal learning outcomes. Therefore, integrating SBS into a comprehensive curriculum path with other educational methods (such as simulation with mannequins or standardized patients) on the same topic is advantageous. This approach enables students to develop a range of technical, behavioral, and relational skills (McKitterick et al. [<reflink idref="bib89" id="ref268">89</reflink>]).</p> <hd id="AN0184623592-39">Limitations</hd> <p>This study has several limitations. First, the control group had fewer participants due to difficulties in recruiting centers in real‐world conditions, which may influence results (Rusticus and Lovato [<reflink idref="bib126" id="ref269">126</reflink>]). While not randomized, which could affect internal validity, the ecological context strengthens external reliability. Effect size, as noted by Cant and Cooper ([<reflink idref="bib25" id="ref270">25</reflink>]), helps reduce heterogeneity in comparisons.</p> <p>Second, SRL profiles were based only on help‐seeking, excluding variables like cognitive strategy change or study time allocation. Personal factors, such as age, prior experience, and gaming profiles (see Blanié, Amorim, et al. [<reflink idref="bib11" id="ref271">11</reflink>]; Ofori [<reflink idref="bib102" id="ref272">102</reflink>]), could have also predicted performance. Increasingly, digital trace data are used to assess actual student behavior rather than self‐report measures.</p> <p>A third limitation is the standardized help provided after errors, which lacked specificity (Huet et al. [<reflink idref="bib58" id="ref273">58</reflink>]). Digital trace analysis could have tailored support for help‐avoidant students (Raković et al. [<reflink idref="bib116" id="ref274">116</reflink>]). Medicactiv did not track the frequency and numbers of attempts, limiting insight into performance differences. Mental workload, as suggested by Paas and Van Merriënboer ([<reflink idref="bib104" id="ref275">104</reflink>]), could have been measured. Eye‐tracking could further illuminate cognitive load during SBS versus traditional education.</p> <p>Finally, the simulators' cultural specificity limits their applicability to other French‐speaking regions, such as Morocco, French‐speaking Africa, Switzerland, Belgium, or Canada, due to the cultural specificity of certain terminology, similar to how tools like VSim are unavailable in France (Gu et al. [<reflink idref="bib48" id="ref276">48</reflink>]; Kim et al. [<reflink idref="bib66" id="ref277">66</reflink>]). It is crucial to compare design elements that are truly comparable, minimizing design variability to reduce bias in comparisons. This would also enable the assessment of long‐term effects in clinical practice (as outlined in level 4 of the Kirkpatrick scale; see Kirkpatrick [<reflink idref="bib67" id="ref278">67</reflink>]) or in international studies, by accounting for similar cultural and socio‐educational contexts.</p> <hd id="AN0184623592-40">Conclusion</hd> <p>The present study showed that SBS appeared to be better than traditional education for teaching first‐year nursing students clinical reasoning. This technological and pedagogical innovation makes it possible to enrich students' curricular experiences, increase their self‐efficacy, and train them to self‐assess more accurately. The results of this first study call for additional research on SRL and SRL profiles in order to adapt the display of information to students who would not spontaneously seek help and better support tutors in their use of SBS. The present study is a response to the growing interest in building bridges between two of the most influential research theories in educational psychology (i.e., SRL and cognitive load theory) with the help of computer‐based learning environments. Finally, future research should explore the long‐term effects of SBS on clinical performance in healthcare fields, considering different cultural and educational contexts.</p> <hd id="AN0184623592-41">Author Contributions</hd> <p> <bold>Guillaume Decormeille:</bold> conceptualization, data curation, formal analysis, project administration, investigation, writing – review and editing, writing – original draft. <bold>Thomas Geeraerts:</bold> conceptualization, methodology, supervision, validation, writing – original draft. <bold>Médéric Descoins:</bold> methodology, data curation, formal analysis, software, supervision, writing – review and editing, writing – original draft. <bold>Nathalie Huet:</bold> conceptualization, writing – original draft, writing – review and editing, validation, methodology, formal analysis, supervision, data curation.</p> <hd id="AN0184623592-42">Acknowledgements</hd> <p>This study was supported by IFSI CHU Bordeaux (Marion Laurent, Florence Gagnerot), IFSI Tulle (Corinne Lescure, Maria Pacheco), IFSI Ussel (Florence Girard), IFSI Pamiers (Jean Michel Cornette, Christine Stervinou), IFSI CHU Toulouse (Thierry Rey), IFSI Niort (Amanda Dubray, Stéphanie Siloret), IFSI Bayonne (Regis Bernard, Nathalie Duvivier), IFSI La Rochelle (Christine Dudognon), IFSI Limoges CRF (Anne Claire Duval, Leila Bentmane), IFSI Aubagne (Astrid Romano), IFSI Castres (Yann Jacquot, Sylvie Marmouget), and IFSI Morlaix (Anne Sophie Messager, Sylvie Thomelin).</p> <hd id="AN0184623592-43">Ethics Statement</hd> <p>This study was approved by the institutional and ethical review board of the University of (Toulouse jean Jaures, No. IRB00011835‐2019‐11‐26‐207).</p> <hd id="AN0184623592-44">Conflicts of Interest</hd> <p>Guillaume Decormeille declares a financial interest with Simforhealth company during the 3 years of the thesis (ministerial agreement for the ANR program research). The other authors declare no conflicts of interest.</p> <hd id="AN0184623592-45">Data Availability Statement</hd> <p>Data are available.</p> <hd id="AN0184623592-46">A Appendix</hd> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/BU8/01mar25/acp70046-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="acp70046-fig-0005.jpg" title="A1 The three phases procedure." /> </p> <p></p> <ref id="AN0184623592-48"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref133" type="bt">1</bibl> <bibtext> Funding: The authors received no specific funding for this work.</bibtext> </blist> </ref> <ref id="AN0184623592-49"> <title> References </title> <blist> <bibtext> Abusubhiah, M., N. Walshe, R. Creedon, B. Noonan, and J. Hegarty. 2023. " Self‐Efficacy in the Context of Nursing Education and Transition to Practice as a Registered Practitioner: A Systematic Review." 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| Header | DbId: eric DbLabel: ERIC An: EJ1468393 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Screen-Based Simulation in Nursing School: Help Use and Self-Regulated Learning – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Guillaume+Decormeille%22">Guillaume Decormeille</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7084-4856">0000-0001-7084-4856</externalLink>)<br /><searchLink fieldCode="AR" term="%22Thomas+Geeraerts%22">Thomas Geeraerts</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6938-0967">0000-0002-6938-0967</externalLink>)<br /><searchLink fieldCode="AR" term="%22Médéric+Descoins%22">Médéric Descoins</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8864-8017">0000-0002-8864-8017</externalLink>)<br /><searchLink fieldCode="AR" term="%22Nathalie+Huet%22">Nathalie Huet</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5209-9127">0000-0001-5209-9127</externalLink>) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Applied+Cognitive+Psychology%22"><i>Applied Cognitive Psychology</i></searchLink>. 2025 39(2). – Name: Avail Label: Availability Group: Avail Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 19 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Nursing+Education%22">Nursing Education</searchLink><br /><searchLink fieldCode="DE" term="%22Nursing+Students%22">Nursing Students</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Simulation%22">Computer Simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Assisted+Instruction%22">Computer Assisted Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Achievement+Gains%22">Achievement Gains</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Management%22">Self Management</searchLink><br /><searchLink fieldCode="DE" term="%22Independent+Study%22">Independent Study</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Difficulty+Level%22">Difficulty Level</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+Learning%22">Visual Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Aural+Learning%22">Aural Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22France%22">France</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1002/acp.70046 – Name: ISSN Label: ISSN Group: ISSN Data: 0888-4080<br />1099-0720 – Name: Abstract Label: Abstract Group: Ab Data: Screen-based simulation (SBS) can complement traditional nursing courses. We compared the effect of innovative virtual environments not widespread in French nursing schools on self-efficacy, quiz performance, and self-regulated learning behaviors. This quasi-experimental study involved 1183 student nurses. Participants were divided into an experimental group (SBS training; n = 894) and a control group (textual content; n = 289). SBS group performed significantly better than controls (p < 0.001) and improved over time (p < 0.001). Controls performed worse over time (p < 0.001). In the control group, a single medium may have overloaded sensory channels, while SBS spread cognitive load across auditory and visual channels. SBS was more effective than traditional teaching and enhanced self-efficacy. This initial study is encouraging, suggesting further investigation into SBS in training and the analysis of learning behaviors through digital data. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2025 – Name: AN Label: Accession Number Group: ID Data: EJ1468393 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/acp.70046 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 19 Subjects: – SubjectFull: Foreign Countries Type: general – SubjectFull: Nursing Education Type: general – SubjectFull: Nursing Students Type: general – SubjectFull: Computer Simulation Type: general – SubjectFull: Computer Assisted Instruction Type: general – SubjectFull: Self Efficacy Type: general – SubjectFull: Achievement Gains Type: general – SubjectFull: Self Management Type: general – SubjectFull: Independent Study Type: general – SubjectFull: Cognitive Processes Type: general – SubjectFull: Difficulty Level Type: general – SubjectFull: Visual Learning Type: general – SubjectFull: Aural Learning Type: general – SubjectFull: Teaching Methods Type: general – SubjectFull: Program Effectiveness Type: general – SubjectFull: France Type: general Titles: – TitleFull: Screen-Based Simulation in Nursing School: Help Use and Self-Regulated Learning Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Guillaume Decormeille – PersonEntity: Name: NameFull: Thomas Geeraerts – PersonEntity: Name: NameFull: Médéric Descoins – PersonEntity: Name: NameFull: Nathalie Huet IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 0888-4080 – Type: issn-electronic Value: 1099-0720 Numbering: – Type: volume Value: 39 – Type: issue Value: 2 Titles: – TitleFull: Applied Cognitive Psychology Type: main |
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