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Primary School Teachers' Classroom-Based E-Assessment Practices: Insights from the Theory of Planned Behaviour

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Title: Primary School Teachers' Classroom-Based E-Assessment Practices: Insights from the Theory of Planned Behaviour
Language: English
Authors: Ying Zhan, Daner Sun (ORCID 0000-0002-9813-6306), Ho Man Kong, Ye Zeng
Source: British Journal of Educational Technology. 2024 55(6):2740-2759.
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: 20
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Education
Descriptors: Elementary School Teachers, Student Evaluation, Evaluation Methods, Educational Technology, Behavior Theories, Foreign Countries, Intention, Predictor Variables, Alternative Assessment, Feedback (Response), Teacher Attitudes
Geographic Terms: Hong Kong
DOI: 10.1111/bjet.13478
ISSN: 0007-1013
1467-8535
Abstract: There is a global trend in the increased adoption of e-assessment in school classrooms to enhance learning. Teachers, as classroom-based assessment designers and implementers, play a vital role in such assessment change. However, little is known about school teachers' classroom-based e-assessment practices and the underlying reasons. To address this research gap, this study identified the factors influencing Hong Kong primary school teachers' e-assessment practices underpinned by the theory of planned behaviour (TPB). A large-scale survey was issued to 878 teachers via Qualtrics. Structural equation modelling (SEM) analysis shows that primary school teachers' intentions of using e-assessment and perceived behavioural control of it were the two strongest factors predicting their e-assessment practices in a general way. Specifically, teachers' intentions outweighed perceived behavioural control in determining their use of alternative e-assessment tasks and e-feedback, but this reversed for e-tests/exercises. The impact of perceived behavioural control was consistent across the three types of e-assessment practices. Furthermore, teachers' attitudes significantly influenced their intentions to use alternative e-assessment tasks, while subject norms primarily predicted their intentions to use e-feedback. The findings have implications for primary schools to take countermeasures to facilitate the successful implementation of e-assessment at the classroom level.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1443081
Database: ERIC
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  Value: <anid>AN0180170783;58i01nov.24;2024Oct11.05:21;v2.2.500</anid> <title id="AN0180170783-1">Primary school teachers' classroom‐based e‐assessment practices: Insights from the theory of planned behaviour </title> <p>There is a global trend in the increased adoption of e‐assessment in school classrooms to enhance learning. Teachers, as classroom‐based assessment designers and implementers, play a vital role in such assessment change. However, little is known about school teachers' classroom‐based e‐assessment practices and the underlying reasons. To address this research gap, this study identified the factors influencing Hong Kong primary school teachers' e‐assessment practices underpinned by the theory of planned behaviour (TPB). A large‐scale survey was issued to 878 teachers via Qualtrics. Structural equation modelling (SEM) analysis shows that primary school teachers' intentions of using e‐assessment and perceived behavioural control of it were the two strongest factors predicting their e‐assessment practices in a general way. Specifically, teachers' intentions outweighed perceived behavioural control in determining their use of alternative e‐assessment tasks and e‐feedback, but this reversed for e‐tests/exercises. The impact of perceived behavioural control was consistent across the three types of e‐assessment practices. Furthermore, teachers' attitudes significantly influenced their intentions to use alternative e‐assessment tasks, while subject norms primarily predicted their intentions to use e‐feedback. The findings have implications for primary schools to take countermeasures to facilitate the successful implementation of e‐assessment at the classroom level.Practitioner notesWhat is already known about this topicE‐assessment has the potential to influence learning.E‐assessment has often been used in a controlled environment with a relatively small sample size.The past 3 years have seen a surge in discussions and research around using e‐assessment in classroom settings, mostly in higher education.What this paper addsPrimary school teachers used more e‐tests or exercises than alternative e‐assessment tasks and e‐feedback in their daily teaching.Teachers' intentions outweighed perceived behavioural control in determining their use of alternative e‐assessment tasks and e‐feedback, but this reversed for e‐tests/exercises.Teachers' attitudes significantly influenced their intentions to use alternative e‐assessment tasks, while subject norms primarily predicted their intentions to use e‐feedback.Implications for practice and/or policyTeachers' intentions of using alternative e‐assessment and e‐feedback should be increased to enhance their usage in the classroom.Teachers' e‐assessment literacy should be developed to enable them to integrate e‐assessment into their daily instruction.</p> <p>Keywords: alternative e‐assessment tasks; e‐feedback; e‐tests/exercises; primary school teachers; theory of planned behaviour</p> <hd id="AN0180170783-2">INTRODUCTION</hd> <p>The growing adoption of information and communication technologies in assessment has become a global school trend. In a comprehensive systematic review of the studies that spanned more than 30 countries conducted by Chen et al. ([<reflink idref="bib8" id="ref1">8</reflink>], p. 1), it is shown that e‐assessment significantly improves 'accuracy of evaluation, comprehensibility, participation, interaction and communication between teachers and parents'. Nevertheless, despite the advantages of e‐assessment, as demonstrated in numerous studies, it has typically been perceived as limited to laboratory environments and is seldom utilised by teachers in actual classrooms with a large number of students (Zhan & So, [<reflink idref="bib53" id="ref2">53</reflink>]). The outbreak of the COVID‐19 pandemic pushed teachers to adopt e‐assessment in the classroom as a new normal of assessment, which creates good opportunities for researchers to investigate this underexplored area.</p> <p>The past 3 years have seen a surge in discussions and research around using e‐assessment in classroom settings. The majority of this research primarily focused on the context of higher education (eg, Kharbat & Abu Daabes, [<reflink idref="bib21" id="ref3">21</reflink>]; Slade et al., [<reflink idref="bib37" id="ref4">37</reflink>]; St‐Onge et al., [<reflink idref="bib40" id="ref5">40</reflink>]). Little is known about how school teachers, especially primary school teachers, adopt e‐assessment in classrooms (Zhan et al., [<reflink idref="bib54" id="ref6">54</reflink>]). Primary school teachers probably encounter more difficulties in implementing e‐assessment due to their lack of necessary e‐assessment experiences and their students, who are typically less mature and more reliant than adolescent and adult learners (Panadero et al., [<reflink idref="bib32" id="ref7">32</reflink>]). Thus, they represent a group that could particularly benefit from focused research attention due to their potential vulnerability in e‐assessment practices.</p> <p>The COVID‐19 pandemic encouraged teachers to adopt e‐assessment tasks in their classrooms (Yang & Xin, [<reflink idref="bib50" id="ref8">50</reflink>]). However, it is crucial not to overlook the roles of teachers, their intentions, beliefs and competencies in this shift towards e‐assessment (Brown et al., [<reflink idref="bib7" id="ref9">7</reflink>]; Chen et al., [<reflink idref="bib8" id="ref10">8</reflink>]; Rink & Mitchell, [<reflink idref="bib34" id="ref11">34</reflink>]; Yan et al., [<reflink idref="bib49" id="ref12">49</reflink>]; Yan & Cheng, [<reflink idref="bib48" id="ref13">48</reflink>]). Presently, there is inadequate understanding of how these factors influence teachers' e‐assessment practices. To successfully promote e‐assessment at the classroom level, it is important to comprehend the reasons why teachers choose specific types of e‐assessment in their daily instructions.</p> <p>To address the above‐mentioned research gaps, this study investigated Hong Kong primary school teachers' e‐assessment practices during school lockdowns caused by the COVID‐19 pandemic and the relationship among teachers' intentions, attitudes, subjective norms, perceived behavioural control and practices regarding e‐assessment underpinned by the framework of the Theory of Planned Behaviour (Ajzen, [<reflink idref="bib2" id="ref14">2</reflink>]). Two specific research questions are proposed as follows.</p> <p></p> <ulist> <item> What kind of e‐assessment practices do Hong Kong primary school teachers conduct in classrooms?</item> <p></p> <item> How do Hong Kong primary school teachers' intentions, attitudes, subjective norms and perceived behavioural control regarding e‐assessment affect their relevant practices in classrooms?</item> </ulist> <hd id="AN0180170783-3">SCHOOL TEACHERS' CLASSROOM‐BASED E‐ASSESSMENT PRACTICES</hd> <p>E‐assessment in classrooms encompasses various digital forms such as online assignment submission for grading, evaluation of an electronic portfolio or personal blog, feedback via computer‐recorded audio files and computer‐graded quizzes (Jordan, [<reflink idref="bib20" id="ref15">20</reflink>]). Essentially, e‐assessment is a formal evaluation method in classrooms using information and communication technology. It allows teachers to measure student learning within a specific period and continuously track their learning progress, offering personalised assistance when needed (Huber & Helm, [<reflink idref="bib18" id="ref16">18</reflink>]). Besides its evaluative and instructional functions, e‐assessment fosters students' learning engagement and online collaboration with minimal traditional limitations on location and timing (Timmis et al., [<reflink idref="bib42" id="ref17">42</reflink>]).</p> <p>In classrooms, e‐assessment is predominantly used in three ways. First, it enables educators to transform conventional paper‐and‐pencil tests into digital formats. Although e‐tests often utilise standardised, multiple‐choice questions (Stödberg, [<reflink idref="bib39" id="ref18">39</reflink>]), the technology can also facilitate the creation of real‐world problems and better evaluate higher‐order thinking skills through the establishment of virtual and immersive environments (Gee & Shaffer, [<reflink idref="bib14" id="ref19">14</reflink>]; Hickey et al., [<reflink idref="bib16" id="ref20">16</reflink>]). Second, teachers employ alternative e‐assessment tasks other than e‐tests or exercises like, e‐portfolios, blogs, wiki projects and forums in their instruction (Jordan, [<reflink idref="bib20" id="ref21">20</reflink>]). Alternative e‐assessment boosts student engagement, collaboration and reflection (Bennett et al., [<reflink idref="bib5" id="ref22">5</reflink>]; Zhan et al., [<reflink idref="bib55" id="ref23">55</reflink>]). Lastly, teachers provide e‐feedback on submitted assignments or work. E‐feedback is viewed as a driving force for online learning (Timmis et al., [<reflink idref="bib42" id="ref24">42</reflink>]; Zhan, [<reflink idref="bib52" id="ref25">52</reflink>]). Given the advantages of technology such as timeliness, automatic scoring, documentation, monitoring, convenience and interactivity, e‐assessment is frequently viewed as an innovative method or intervention to which students are exposed in a lab setting (Zhan & So, [<reflink idref="bib53" id="ref26">53</reflink>]). Subsequently, the learning outcomes are often attributed to this exposure. E‐assessment has often been used in a controlled environment with a relatively small sample size.</p> <p>However, the voices and practices of teachers using e‐assessment in real classrooms have largely been overlooked. According to Van den Akker ([<reflink idref="bib43" id="ref27">43</reflink>]), practitioners play crucial roles in identifying approaches and developing principles to address practical and complex problems. Without understanding teachers' concerns and pedagogical use of e‐assessment, a gap may emerge between research, design and practice.</p> <p>During the pandemic, the international community has intensified efforts to transform teaching from offline to online (OECD, [<reflink idref="bib29" id="ref28">29</reflink>]), thereby boosting technology integration into assessment of and for learning. Some studies have begun to examine teachers' practices of e‐assessment at the classroom level. Aslan et al. ([<reflink idref="bib4" id="ref29">4</reflink>]) interviewed 18 secondary school teachers in Turkey, discovering that their assessment methods were restricted to assignments, end‐of‐unit tests and online course participation. Similarly, Neuwirth et al. ([<reflink idref="bib28" id="ref30">28</reflink>]) interviewed 42 secondary school teachers in Sweden. They found that the teachers needed to gather evidence of learning via various assignments, oral exams and tests due to the pressures of national examinations but struggled to provide online feedback. Drijvers et al. ([<reflink idref="bib10" id="ref31">10</reflink>]) distributed questionnaires to 1719 secondary school teachers in Belgium, Germany and the Netherlands to understand their distance teaching practices, including assessment. They found that teachers faced difficulty providing feedback digitally. Sandvik et al. ([<reflink idref="bib36" id="ref32">36</reflink>]) studied the perceptions of Norwegian secondary school students regarding e‐assessment practices, revealing that students had more homework, received less feedback and participated in less group work during COVID‐19 distance learning. However, there is a scarcity of empirical studies focusing on the e‐assessment practices of primary school teachers who work with young, vulnerable learners. One study focusing on this demographic is that of Panadero et al. ([<reflink idref="bib32" id="ref33">32</reflink>]), which included Spanish primary school teachers. Their study found that, compared to higher education instructors, primary school teachers had made more significant changes to their assessment, including lowering standards, demonstrating more flexibility in grading and reducing the use of rubrics and feedback.</p> <p>The existing literature revealed that school teachers have tried to maintain regular teaching routines by adapting their assessment practices for an online environment. It also shows that school teachers tended to differentiate their e‐assessment practices and provide fewer alternative e‐assessment tasks and less e‐feedback than e‐tests or exercises. However, it is still unknown why teachers adopt specific e‐assessment practices at the classroom level.</p> <hd id="AN0180170783-4">THEORETICAL FRAMEWORK: THE THEORY OF PLANNED BEHAVIOUR</hd> <p>This study adopted the theory of planned behaviour (TPB) (Ajzen, [<reflink idref="bib2" id="ref34">2</reflink>]) to explore the reasons underlying teachers' e‐assessment practices. According to this theory, humans' behaviour and intentions are explained by three types of factors (ie, attitudes, subjective norms and perceived behavioural control). Simply stated, if people are inclined to judge a suggested behaviour as positive (attitudes), they believe that the behaviour is also supported by other people in the community (subjective norms) and they are confident to exhibit the behaviour (perceived behavioural control), they are more willing to perform it, which will, in turn, enhance the possibility of real action. The perceived behavioural control may also be translated into actual behaviour directly when people think it is easy to perform.</p> <p>As claimed by Minooei et al. ([<reflink idref="bib27" id="ref35">27</reflink>]), the TPB is a systematic framework to explain the behavioural choices of humans. This theory has been successfully applied to study intention and behaviour in various fields, such as educational technology (Lee et al., [<reflink idref="bib24" id="ref36">24</reflink>]), healthcare (Godin & Kok, [<reflink idref="bib15" id="ref37">15</reflink>]), change management (Jimmieson et al., [<reflink idref="bib19" id="ref38">19</reflink>]) and environmental protection (Wan et al., [<reflink idref="bib44" id="ref39">44</reflink>]). A meta‐analysis conducted by Armitage and Conner ([<reflink idref="bib3" id="ref40">3</reflink>]) revealed that the TPB accounted for 27% and 39% of the variance in behaviour and intention respectively. Recently, The TPB has been used to predict teachers' formative assessment practices and intentions (eg, Yan, [<reflink idref="bib46" id="ref41">46</reflink>]; Yan et al., [<reflink idref="bib49" id="ref42">49</reflink>]; Yan & Cheng, [<reflink idref="bib48" id="ref43">48</reflink>]). These studies have demonstrated the potential of using the TPB in the assessment field. Given the validity and effectiveness of using the TPB to explain human intention and behaviour, adopting it as the theoretical framework of this study could generate deeper insights into the rationales underlying primary school teachers' behaviour regarding e‐assessment. Figure 1 demonstrates the hypothesised TPB model predicting primary school teachers' e‐assessment practices in the classroom.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/58I/01nov24/bjet13478-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="bjet13478-fig-0001.jpg" title="1 A hypothesised TPB model predicting primary school teachers' e‐assessment practices in classrooms." /> </p> <p></p> <p>Although the literature lacks the synthesis of the factors influencing teachers' e‐assessment practices through the lens of the TPB, there is scattered evidence on the relationship between teachers' attitudes, subjective norms, perceived behavioural control, intentions and practices of e‐assessment. Teachers' attitudes towards e‐assessment are largely decided by their beliefs about the effectiveness or consequences of conducting e‐assessment to influence learning and/or teaching. Such attitudes are called instrumental attitudes (Ajzen, [<reflink idref="bib2" id="ref44">2</reflink>]). Previous studies examined teachers' instrumental attitudes towards formative assessment and found that teachers' acknowledgement of the usefulness of formative assessment predicted their intentions to implement it (So & Lee, [<reflink idref="bib38" id="ref45">38</reflink>]; Yan & Cheng, [<reflink idref="bib48" id="ref46">48</reflink>]). Similar findings are reported in the area of e‐assessment. For instance, Lee et al. ([<reflink idref="bib23" id="ref47">23</reflink>]) reported a positive correlation between American school teachers' favourable attitudes towards e‐assessment and its implementation. Similarly, Tang et al. ([<reflink idref="bib41" id="ref48">41</reflink>]) found that Vietnamese teachers' perceived usefulness of e‐assessment predicted their intentions to use it in their classrooms.</p> <p>Subjective norms concern perceived social pressure and other important people's opinions to perform (or not perform) certain behaviour (Ajzen, [<reflink idref="bib2" id="ref49">2</reflink>]). Examination culture, government education policies and internal school policies can potentially exert social pressure on teachers in choosing their assessment practices (Yan & Brown, [<reflink idref="bib47" id="ref50">47</reflink>]; Yin & Buck, [<reflink idref="bib51" id="ref51">51</reflink>]). Teachers' significant others include school principals. parents, students, subject panel heads and colleagues. Ahmedi ([<reflink idref="bib1" id="ref52">1</reflink>]) found that significant others' requests or decisions affected whether teachers implement formative assessment in their classrooms. In a recent study, Panadero et al. ([<reflink idref="bib32" id="ref53">32</reflink>]) found that primary school teachers in Spain, unlike university instructors, experienced less pressure to uphold accountability due to the Spanish government's lenient quality assurance policy in education during the COVID‐19 pandemic. Consequently, primary school teachers adopted a more flexible grading approach and lowered their assessment criteria.</p> <p>Perceived behavioural control is 'the perception of situational competence that leads to the perceived easiness or difficulty while engaging in the behaviour of interest' (Roy et al., [<reflink idref="bib35" id="ref54">35</reflink>], pp. 1016–1017). Teachers' perceived behavioural control of e‐assessment is closely related to their e‐assessment literacy. A teacher with e‐assessment literacy can wisely use various applications and technological systems to assess students and adapt various assessment approaches (Eyal, [<reflink idref="bib12" id="ref55">12</reflink>]). The Zhang and So ([<reflink idref="bib53" id="ref56">53</reflink>]) found that Hong Kong primary school teachers could not judiciously use the data from the assessment platform in their subsequent teaching due to insufficient assessment literacy.</p> <p>The above discussion reveals the potential of using the TPB to explain Hong Kong school teachers' e‐assessment practices in this study. Considering that e‐assessment has different types with different functions, it would be better to establish a structural understanding of teachers' specific types of e‐assessment practices and their influencing factors. This is the major research gap that this study attempted to address.</p> <hd id="AN0180170783-6">METHODOLOGY</hd> <p></p> <hd id="AN0180170783-7">Participants</hd> <p>A stratified random sampling method (Breidt & Opsomer, [<reflink idref="bib6" id="ref57">6</reflink>]) was adopted to recruit subjects to increase the representativeness of the subjects in the survey. Firstly, all the primary schools were divided in terms of their locations, including Hong Kong Island, Kowloon and New Territories. After that, 4% of these primary schools were selected randomly. As indicated in Table 1, the locations of these schools covered Hong Kong Island, Kowloon and New Territories. All the teachers in these schools were invited to complete the survey. In total, 878 teachers were recruited as subjects. The number of survey subjects exceeded the acceptable number calculated according to sampling theory (values calculated at <ulink href="http://www.raosoft.com/samplesize.html">http://www.raosoft.com/samplesize.html</ulink>). In 2019–2020, the Education Bureau ([<reflink idref="bib11" id="ref58">11</reflink>]) reported 27,466 teachers. A sample of 379 teachers is acceptable to achieve a recommended confidence level of 95% and a margin error level of 5%. Table 1 lists the demographic information of the survey participants.</p> <p>1 TABLE Demographic characteristics of the survey participants.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left" /><th align="left">Frequency</th><th align="left">Per cent (%)</th></tr><tr><th align="left">HK</th><th align="left">KLN</th><th align="left">NT</th><th align="left">Total</th><th align="left">HK</th><th align="left">KLN</th><th align="left">NT</th><th align="left">Total</th></tr></thead><tbody valign="top"><tr><td align="left">Gender</td><td align="left">Male</td><td align="left">41</td><td align="left">58</td><td align="left">104</td><td align="left">203</td><td align="char" char=".">22.0%</td><td align="char" char=".">24.4%</td><td align="char" char=".">22.9%</td><td align="char" char=".">23.1%</td></tr><tr><td align="left">Female</td><td align="left">145</td><td align="left">180</td><td align="left">350</td><td align="left">675</td><td align="char" char=".">78.0%</td><td align="char" char=".">75.6%</td><td align="char" char=".">77.1%</td><td align="char" char=".">76.9%</td></tr><tr><td align="left">Years of teaching</td><td align="left">1–5 years</td><td align="left">47</td><td align="left">60</td><td align="left">138</td><td align="left">245</td><td align="char" char=".">25.3%</td><td align="char" char=".">25.2%</td><td align="char" char=".">30.4%</td><td align="char" char=".">27.9%</td></tr><tr><td align="left">6–10 years</td><td align="left">47</td><td align="left">49</td><td align="left">98</td><td align="left">194</td><td align="char" char=".">25.3%</td><td align="char" char=".">20.6%</td><td align="char" char=".">21.6%</td><td align="char" char=".">22.1%</td></tr><tr><td align="left">Above 10 years</td><td align="left">92</td><td align="left">129</td><td align="left">218</td><td align="left">439</td><td align="char" char=".">49.5%</td><td align="char" char=".">54.2%</td><td align="char" char=".">48.0%</td><td align="char" char=".">50.0%</td></tr><tr><td align="left">Key stages of teaching</td><td align="left">Key Stage 1 (Primary 1‐Primary 3)</td><td align="left">71</td><td align="left">80</td><td align="left">176</td><td align="left">327</td><td align="char" char=".">38.2%</td><td align="char" char=".">33.6%</td><td align="char" char=".">38.8%</td><td align="char" char=".">37.2%</td></tr><tr><td align="left">Key Stage 2 (Primary 4‐Primary 6)</td><td align="left">115</td><td align="left">158</td><td align="left">278</td><td align="left">551</td><td align="char" char=".">61.8%</td><td align="char" char=".">66.4%</td><td align="char" char=".">61.2%</td><td align="char" char=".">62.8%</td></tr><tr><td align="left">Subjects taught</td><td align="left">Chinese</td><td align="left">64</td><td align="left">76</td><td align="left">145</td><td align="left">285</td><td align="char" char=".">34.4%</td><td align="char" char=".">31.9%</td><td align="char" char=".">31.9%</td><td align="char" char=".">32.5%</td></tr><tr><td align="left">English</td><td align="left">50</td><td align="left">48</td><td align="left">110</td><td align="left">208</td><td align="char" char=".">26.9%</td><td align="char" char=".">20.2%</td><td align="char" char=".">24.2%</td><td align="char" char=".">23.7%</td></tr><tr><td align="left">Maths</td><td align="left">39</td><td align="left">52</td><td align="left">100</td><td align="left">191</td><td align="char" char=".">21.0%</td><td align="char" char=".">21.8%</td><td align="char" char=".">22.0%</td><td align="char" char=".">21.8%</td></tr><tr><td align="left">GS</td><td align="left">15</td><td align="left">18</td><td align="left">37</td><td align="left">70</td><td align="char" char=".">8.1%</td><td align="char" char=".">7.6%</td><td align="char" char=".">8.1%</td><td align="char" char=".">8.0%</td></tr><tr><td align="left">OS</td><td align="left">18</td><td align="left">44</td><td align="left">62</td><td align="left">124</td><td align="char" char=".">9.7%</td><td align="char" char=".">18.5%</td><td align="char" char=".">13.7%</td><td align="char" char=".">14.1%</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>: HK = Hong Kong Island; KLN = Kowloon; New Territories = NT; GS = General Studies; OS = Other subjects (ie, Mandarin, music, visual arts and physical education).</p> <hd id="AN0180170783-8">The survey</hd> <p>The survey consisted of two sections. One was for collecting participating teachers' demographic information, including gender, years of teaching, stages of teaching, school locations and subjects taught. The other section investigated five aspects: practices, intentions, attitudes, subjective norms and perceived behavioural control of three types of teachers' e‐assessment (ie, e‐tests/exercises, alternative e‐assessment, e‐feedback). Table 2 lists the number of items, the sample items and five aspects of measurement. The items about intentions, attitudes, subjective norms and perceived behavioural control were rated on a 6‐point Likert scale of agreement (ie, strongly degree, agree, slightly agree, slightly disagree, disagree and strongly disagree). The items about three dimensions of practice were rated on a 6‐point Likert scale of frequency (ie, always, often, sometimes, occasionally, seldom and never).</p> <p>2 TABLE The structure and sample items of primary school teachers' e‐assessment survey.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Scales</th><th align="left">No. of items</th><th align="left">Sample item</th><th align="left">Alpha coefficients</th><th align="left">Omega total</th><th align="left">Coefficient <italic>H</italic></th></tr></thead><tbody valign="top"><tr><td align="left">Practices</td><td align="left">E‐tests/exercises practices</td><td align="left">5</td><td align="left">Assign students to do e‐exercises to preview a lesson</td><td align="char" char=".">0.830</td><td align="char" char=".">0.831</td><td align="char" char=".">0.853</td></tr><tr><td align="left">Alternative e‐assessment practices</td><td align="left">4</td><td align="left">Ask students to discuss in groups on the teaching platform</td><td align="char" char=".">0.822</td><td align="char" char=".">0.829</td><td align="char" char=".">0.834</td></tr><tr><td align="left">E‐feedback practices</td><td align="left">4</td><td align="left">Give feedback to students via social media</td><td align="char" char=".">0.740</td><td align="char" char=".">0.743</td><td align="char" char=".">0.754</td></tr><tr><td align="left">Intentions</td><td align="left">Intentions of using e‐tests/exercises</td><td align="left">4</td><td align="left">Assign students to do self‐developed online exercises or homework</td><td align="char" char=".">0.820</td><td align="char" char=".">0.827</td><td align="char" char=".">0.842</td></tr><tr><td align="left">Intentions of using alternative e‐assessment tasks</td><td align="left">4</td><td align="left">Use online group discussions to evaluate the students' understanding of knowledge</td><td align="char" char=".">0.820</td><td align="char" char=".">0.830</td><td align="char" char=".">0.842</td></tr><tr><td align="left">Intentions of using e‐feedback</td><td align="left">4</td><td align="left">Give feedback to students on the online message board in the learning management platform</td><td align="char" char=".">0.850</td><td align="char" char=".">0.855</td><td align="char" char=".">0.860</td></tr><tr><td align="left">Attitudes</td><td align="left">Attitude towards using e‐tests/exercises</td><td align="left">4</td><td align="left">E‐tests/exercises can reduce teachers' workload</td><td align="char" char=".">0.746</td><td align="char" char=".">0.761</td><td align="char" char=".">0.768</td></tr><tr><td align="left">Attitude towards using alternative e‐assessment tasks</td><td align="left">4</td><td align="left">Alternative e‐assessment can increase students' participation in online classes</td><td align="char" char=".">0.856</td><td align="char" char=".">0.858</td><td align="char" char=".">0.874</td></tr><tr><td align="left">Attitude towards using teacher e‐feedback</td><td align="left">4</td><td align="left">E‐feedback facilitates students' review and reflection</td><td align="char" char=".">0.828</td><td align="char" char=".">0.829</td><td align="char" char=".">0.831</td></tr><tr><td align="left">Subjective norms</td><td align="left">Subjective norms of using e‐tests/exercises</td><td align="left">4</td><td align="left">The school encourages us to use the online platform to assign e‐tests/exercises</td><td align="char" char=".">0.769</td><td align="char" char=".">0.769</td><td align="char" char=".">0.770</td></tr><tr><td align="left">Subjective norms of using alternative e‐assessment tasks</td><td align="left">4</td><td align="left">My students actively participate in alternative e‐assessment</td><td align="char" char=".">0.827</td><td align="char" char=".">0.828</td><td align="char" char=".">0.831</td></tr><tr><td align="left">Subjective norms of using e‐feedback</td><td align="left">4</td><td align="left">Students value our e‐feedback</td><td align="char" char=".">0.822</td><td align="char" char=".">0.823</td><td align="char" char=".">0.837</td></tr><tr><td align="left">Perceived behavioural control</td><td align="left">Perceived behavioural control of e‐tests/exercises</td><td align="left">3</td><td align="left">I can design high‐quality e‐tests/exercises</td><td align="char" char=".">0.800</td><td align="char" char=".">0.801</td><td align="char" char=".">0.803</td></tr><tr><td align="left">Perceived behavioural control of alternative e‐assessment tasks</td><td align="left">3</td><td align="left">I can design high‐quality alternative e‐assessment activities</td><td align="char" char=".">0.908</td><td align="char" char=".">0.909</td><td align="char" char=".">0.913</td></tr><tr><td align="left">Perceived behavioural control of e‐feedback</td><td align="left">3</td><td align="left">I am proficient in using a variety of e‐feedback methods</td><td align="char" char=".">0.774</td><td align="char" char=".">0.774</td><td align="char" char=".">0.793</td></tr></tbody></table> </ephtml> </p> <p>Cronbach's alpha reliability coefficients for all scales were calculated and are listed in Table 2, all of which are above 0.70. Since using Cronbach's alpha coefficient as the indicator of reliability may make measures appear less reliable than they actually are (McNeish, [<reflink idref="bib26" id="ref59">26</reflink>]; Padilla & Divers, [<reflink idref="bib30" id="ref60">30</reflink>]), the omega total and the coefficient H of each scale are also reported in Table 2. All of the reliability indicators reported in Table 2 showed that the scales used in this study had good reliability. To check the within‐network validity of the five scales in this project, an item‐to‐scale correlation was conducted. The mean correlations of all scales were from 0.750 to 0.807 for practices, from 0.804 to 0.832 for intentions, from 0.757 to 0.838 for attitudes, from 0.769 to 0.812 for subjective norms and from 0.832 and 0.920 for perceived behavioural control, which was all above the minimum acceptance level of 0.30. Therefore, these scales all had good internal consistency within each dimension (Gable & Wolf, [<reflink idref="bib13" id="ref61">13</reflink>]). As indicated in Figure 2, confirmatory Factor Analysis (CFA) was also used to examine the construct validity of the e‐assessment practice scale, which supported the three‐dimensional structure (<emph>χ</emph><sups>2</sups>/df = 6.983, <emph>p</emph> < 0.001; IFI = 0.921; TLI = 0.900; CFI = 0.920; PNFI = 0.722; RMSEA = 0.083; SRMR = 0.051). All items' factor loadings on the three dimensions were statistically significant and above the recommended minimum of 0.30 (Kline, [<reflink idref="bib22" id="ref62">22</reflink>]).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/58I/01nov24/bjet13478-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="bjet13478-fig-0002.jpg" title="2 CFA for teachers' e‐assessment practices." /> </p> <p></p> <hd id="AN0180170783-10">Data analysis</hd> <p>Cronbach's alpha coefficients, the omega total and the coefficient H were first calculated for the survey constructs. The item‐to‐scale correlations were then used to estimate the validity of the involved constructs. In addition, confirmatory factor analysis (CFA) was also used to examine the construct validity of each scale. The means of each construct in the survey were calculated to indicate the current state of teachers' e‐assessment practices, intentions and influencing factors.</p> <p>Structural equation modelling (SEM) was conducted to generate a more accurate estimation of influencing factors. When performing the SEM analyses, three models were generated, in which teachers' intentions and practices regarding three types of e‐assessment (ie, e‐tests/exercises, alternative e‐assessment, e‐feedback) were, respectively, defined as the dependent variables. We utilised maximum likelihood estimation in our analysis, which can generally provide more accurate estimates of factor loadings and robust standard errors when using data from a 6‐point Likert scale (Rhemtulla et al., [<reflink idref="bib33" id="ref63">33</reflink>]). Numerous fit indices are used in SEM, the most common of which is the ratio of the chi‐square statistic (Lehman et al., [<reflink idref="bib25" id="ref64">25</reflink>]). Other fit indices commonly calculated in SEM are the root mean square error of approximation (RMSEA), the parsimonious normed fit index (PNFI), the comparative fit index (CFI) and standardised root mean square residual (SRMR). The criterion values are set based on Hu and Bentler's ([<reflink idref="bib17" id="ref65">17</reflink>]) prescription. The <emph>χ</emph><sups>2</sups>/df should be below three and above 1. For the RMSEA, 0.05 and below is assumed to be the best fit, and 0.08 and below is assumed to be a good fit. For the PNFI, 0.50 and above is assumed to be a good fit. For the CFI, 0.90 and above is assumed to be a good fit. For SRMR, 05 and below is assumed to be the best fit, and 0.08 and below is assumed to be a good fit. These five fit indices were used as indicators of model fit in this study. The bootstrapping method was adopted in the analysis to address possible non‐normality of the data. SEM was conducted using AMOS 25, and other statistical analysis mentioned before was conducted via SPSS 25.</p> <hd id="AN0180170783-11">FINDINGS</hd> <p></p> <hd id="AN0180170783-12">The current state of primary school teachers' e‐assessment practices and influencing factors</hd> <p>Table 3 provides a descriptive analysis of teachers' e‐assessment practices, intentions, attitudes, subjective norms and perceived behavioural control. Out of the three types of e‐assessment practices, e‐tests/exercises were most frequently conducted by teachers (<emph>M</emph> = 4.03, <emph>SD</emph> = 0.84), followed by alternative e‐assessment tasks (<emph>M</emph> = 3.42, <emph>SD</emph> = 0.99) and e‐feedback (<emph>M</emph> = 3.41, <emph>SD</emph> = 0.98). A similar pattern was identified in terms of teachers' intentions of using e‐tests/exercises (<emph>M</emph> = 4.66, <emph>SD</emph> = 0.65), alternative e‐assessment tasks (<emph>M</emph> = 4.38, <emph>SD</emph> = 0.78) and e‐feedback (<emph>M</emph> = 4.26, <emph>SD</emph> = 0.86). Teachers recognised the most value in using e‐tests/exercises (<emph>M</emph> = 4.62, <emph>SD</emph> = 0.66), then alternative e‐assessment tasks (<emph>M</emph> = 4.35, <emph>SD</emph> = 0.70), and finally, teacher e‐feedback (<emph>M</emph> = 4.24, <emph>SD</emph> = 0.73). Moreover, they felt the most social pressure and valued others' opinions on using e‐tests/exercises in the classroom (<emph>M</emph> = 4.51, <emph>SD</emph> = 0.67). This was followed by the use of alternative e‐assessment tasks (<emph>M</emph> = 4.14, <emph>SD</emph> = 0.74) and e‐feedback (<emph>M</emph> = 4.11, <emph>SD</emph> = 0.76). Teachers also felt they had the most control over their e‐test/exercise practices (<emph>M</emph> = 4.27, <emph>SD</emph> = 0.76), followed by e‐feedback (<emph>M</emph> = 4.20, <emph>SD</emph> = 0.73) and alternative e‐assessment tasks (<emph>M</emph> = 4.11, <emph>SD</emph> = 0.82).</p> <p>3 TABLE The descriptive analysis of primary school teachers' e‐assessment practices and influencing factors.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Scales</th><th align="left">Minimum</th><th align="left">Maximum</th><th align="left">Mean</th><th align="left">Std. deviation</th></tr></thead><tbody valign="top"><tr><td align="left">Practices</td><td align="left">E‐tests/exercises practices</td><td align="char" char=".">1.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.03</td><td align="char" char=".">0.84</td></tr><tr><td align="left">Alternative e‐assessment practices</td><td align="char" char=".">1.00</td><td align="char" char=".">6.00</td><td align="char" char=".">3.42</td><td align="char" char=".">0.99</td></tr><tr><td align="left">E‐feedback practices</td><td align="char" char=".">1.00</td><td align="char" char=".">6.00</td><td align="char" char=".">3.41</td><td align="char" char=".">0.98</td></tr><tr><td align="left">Intentions</td><td align="left">Intentions of using e‐tests/exercises</td><td align="char" char=".">2.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.66</td><td align="char" char=".">0.65</td></tr><tr><td align="left">Intentions of using alternative e‐assessment tasks</td><td align="char" char=".">1.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.38</td><td align="char" char=".">0.78</td></tr><tr><td align="left">Intentions of using e‐feedback</td><td align="char" char=".">1.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.26</td><td align="char" char=".">0.86</td></tr><tr><td align="left">Attitudes</td><td align="left">Attitudes towards using e‐tests/exercises</td><td align="char" char=".">2.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.62</td><td align="char" char=".">0.66</td></tr><tr><td align="left">Attitudes towards using alternative e‐assessment tasks</td><td align="char" char=".">1.75</td><td align="char" char=".">6.00</td><td align="char" char=".">4.35</td><td align="char" char=".">0.70</td></tr><tr><td align="left">Attitudes towards using teacher e‐feedback</td><td align="char" char=".">1.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.24</td><td align="char" char=".">0.73</td></tr><tr><td align="left">Subjective norms</td><td align="left">Subjective norms of using e‐tests/exercises</td><td align="char" char=".">2.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.51</td><td align="char" char=".">0.67</td></tr><tr><td align="left">Subjective norms of using alternative e‐assessment tasks</td><td align="char" char=".">1.25</td><td align="char" char=".">6.00</td><td align="char" char=".">4.14</td><td align="char" char=".">0.74</td></tr><tr><td align="left">Subjective norms of using e‐feedback</td><td align="char" char=".">1.25</td><td align="char" char=".">6.00</td><td align="char" char=".">4.11</td><td align="char" char=".">0.76</td></tr><tr><td align="left">Perceived behavioural control</td><td align="left">Perceived behavioural control of e‐tests/exercises</td><td align="char" char=".">1.33</td><td align="char" char=".">6.00</td><td align="char" char=".">4.27</td><td align="char" char=".">0.76</td></tr><tr><td align="left">Perceived behavioural control of alternative e‐assessment tasks</td><td align="char" char=".">1.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.11</td><td align="char" char=".">0.82</td></tr><tr><td align="left">Perceived behavioural control of e‐feedback</td><td align="char" char=".">2.00</td><td align="char" char=".">6.00</td><td align="char" char=".">4.20</td><td align="char" char=".">0.73</td></tr></tbody></table> </ephtml> </p> <hd id="AN0180170783-13">Significant predictors of primary school teachers' e‐test/exercise practices</hd> <p>Figure 3 illustrates the model for teachers' use of e‐tests/exercises. The model fit indices (<emph>χ</emph><sups>2</sups>/df = 5.160, <emph>p</emph> < 0.001; IFI = 0.907; TLI = 0.891; CFI = 0.907; PNFI = 0.757; RMSEA = 0.069; SRMR = 0.049) suggest a strong alignment with the data. Teachers' attitudes (<emph>β</emph> = 0.32, <emph>p</emph> < 0.001), subjective norms (<emph>β</emph> = 0.18, <emph>p</emph> < 0.001) and perceived behavioural control (<emph>β</emph> = 0.29, <emph>p</emph> < 0.001) significantly and positively influenced their intentions. Moreover, teachers' intentions (<emph>β</emph> = 0.21, <emph>p</emph> < 0.001) and perceived behavioural control (<emph>β</emph> = 0.38, <emph>p</emph> < 0.001) had a significant and positive effect on their e‐test/exercise practices.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/58I/01nov24/bjet13478-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="bjet13478-fig-0003.jpg" title="3 A model predicting primary teachers' use of e‐tests/exercises in classrooms. Standardised path coefficients were shown. ***p < 0.001, **p < 0.01, *p < 0.05." /> </p> <p></p> <hd id="AN0180170783-15">Significant predictors of primary school teachers' alternative e‐assessment practices</hd> <p>The structural understanding of teachers' alternative e‐assessment practices and their influencing factors was established, and the model of alternative e‐assessment practices is shown in Figure 4. Model fit indices (<emph>χ</emph><sups>2</sups>/df = 5.468, <emph>p</emph> < 0.001; IFI = 0.932; TLI = 0.932; CFI = 0.932; PNFI = 0.773; RMSEA = 0.071; SRMR = 0.043) suggest a good model fit. Results indicated that teachers' attitudes (<emph>β</emph> = 0.44, <emph>p</emph> < 0.001) and perceived behavioural control (<emph>β</emph> = 0.23, <emph>p</emph> < 0.001) had significant positive impacts on teachers' intentions. However, the positive impacts of subjective norms (<emph>β</emph> = 0.07, <emph>p</emph> = 0.431) on teachers' intentions were insignificant. In addition, teachers' intentions (<emph>β</emph> = 0.44, <emph>p</emph> < 0.001) and perceived behavioural control (<emph>β</emph> = 0.32, <emph>p</emph> < 0.001) had significant positive impacts on teachers' alternative e‐assessment practices.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/58I/01nov24/bjet13478-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="bjet13478-fig-0004.jpg" title="4 A model predicting primary teachers' use of alternative e‐assessment tasks in classrooms. Standardised path coefficients were shown. ***p < 0.001, **p < 0.01, *p < 0.05. The dotted lines were statistically insignificant." /> </p> <p></p> <hd id="AN0180170783-17">Significant predictors of primary school teachers' e‐feedback practices</hd> <p>Model fit indices (<emph>χ</emph><sups>2</sups>/df = 6.539, <emph>p</emph> < 0.001; IFI = 0.901; TLI = 0.882; CFI = 0.901; PNFI = 0.743; RMSEA = 0.079; SRMR = 0.046) indicate that the model of e‐feedback practices fits the data well (see Figure 5). Results revealed that subjective norms (<emph>β</emph> = 0.42, <emph>p</emph> < 0.001) and perceived behavioural control (<emph>β</emph> = 0.17, <emph>p</emph> < 0.001) had significant positive impacts on teachers' intentions. However, the positive impacts of attitudes (<emph>β</emph> = 0.06, <emph>p</emph> = 0.499) on teachers' intentions were not significant. In addition, teachers' intentions (<emph>β</emph> = 0.54, <emph>p</emph> < 0.001) and perceived behavioural control (<emph>β</emph> = 0.30, <emph>p</emph> < 0.001) had significant positive effects on teachers' e‐feedback practices.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/58I/01nov24/bjet13478-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="bjet13478-fig-0005.jpg" title="5 A model predicting primary teachers' use of e‐feedback in classrooms. Standardised path coefficients were shown. ***p < 0.001, **p < 0.01, *p < 0.05. The dotted lines were statistically insignificant." /> </p> <p></p> <p>In sum. the results indicate that teachers' attitudes played the most important role in determining their intention of using alternative e‐assessment tasks, while subject norms are the most crucial predictor of their intentions of using e‐feedback. It was also found that teachers' intentions were more important than perceived behavioural control in predicting their alternative e‐assessment and e‐feedback practices, while it was vice versa for the situation of using e‐tests/exercises. In addition, the impacts of perceived behavioural control were similar across three types of e‐assessment practices.</p> <hd id="AN0180170783-19">DISCUSSION AND CONCLUSION</hd> <p>This study investigated Hong Kong primary school teachers' e‐assessment practices in classrooms. The findings reveal that the participants used more e‐tests or exercises than alternative e‐assessment tasks and e‐feedback in their daily teaching. This finding echoes previous studies in different countries during school lockdowns (eg, Aslan et al., [<reflink idref="bib4" id="ref66">4</reflink>]; Drijvers et al., [<reflink idref="bib10" id="ref67">10</reflink>]; Neuwirth et al., [<reflink idref="bib28" id="ref68">28</reflink>]; Panadero et al., [<reflink idref="bib32" id="ref69">32</reflink>]; Sandvik et al., [<reflink idref="bib36" id="ref70">36</reflink>]). The imbalance in using different types of e‐assessment in classrooms seems to be an international phenomenon and worth in‐depth investigation of influencing factors, which were the focus of this study.</p> <p>The TPB was used as a theoretical framework to guide the identification of the predictors of different types of e‐assessment practices. It explains primary school teachers' usage of e‐tests/exercises with good model fit. Participants' attitudes, subject norms and perceived behavioural control regarding e‐tests/exercises influenced their intentions to use them and, in turn, determined how often they used them. In addition, the participants' perceived behavioural control of e‐tests/exercises directly influenced their usage. It is noteworthy that the effect of perceived behavioural control on teachers' e‐tests/exercise practices was bigger than that of intentions. The reason might be that e‐tests/exercises were straightforward for the participants, which they usually did in classrooms but in different modes. Hong Kong is an examination‐oriented education system, and teachers are accustomed to doing tests or exercises in their classrooms (Yan & Brown, [<reflink idref="bib47" id="ref71">47</reflink>]). Therefore, their perceived behavioural control of e‐tests/exercises played a more important role in determining their corresponding practices than their intentions. This finding implies the necessity of cultivating teachers' e‐assessment literacy in designing e‐tests/exercises and interpreting the big data automatically generated by the assessment platform, which echoes the finding of Zhan and So ([<reflink idref="bib53" id="ref72">53</reflink>]).</p> <p>However, when predicting teachers' alternative e‐assessment and e‐feedback practices, the impact of teachers' intentions was larger than that of perceived behavioural control. This interesting finding can be interpreted by considering the effort and volition teachers need to perform those two types of e‐assessment. Intentions are assumed to encapsulate the motivational elements that shape behaviour and demonstrate the level of effort individuals are willing to apply or the extent of their determination to execute the behaviour (Ajzen, [<reflink idref="bib2" id="ref73">2</reflink>]). Alternative e‐assessment tasks and e‐feedback are the activities teachers need to spend much more time and effort preparing and implementing than e‐tests/exercises, which are comparatively easier to do in classrooms. For example, in another qualitative study by Zhan et al. ([<reflink idref="bib54" id="ref74">54</reflink>]), Hong Kong primary school teachers mentioned that alternative e‐assessment tasks caused their heavy workload. Compared with e‐tests/exercises, students' disengagement in alternative e‐assessment tasks and e‐feedback seems more obvious because students may be easily distracted while working online for a longer time and may lack self‐discipline and self‐regulation strategies to monitor their alternative e‐assessment process and act on e‐feedback (eg, Pan et al., [<reflink idref="bib31" id="ref75">31</reflink>]; Panadero et al., [<reflink idref="bib32" id="ref76">32</reflink>]; Zhan et al., [<reflink idref="bib54" id="ref77">54</reflink>]). However, the above explanation is tentative and needs more empirical evidence to support it.</p> <p>This study found that teachers' attitudes significantly influenced their intentions to use alternative e‐assessment tasks. This finding echoes the argument by Ajzen ([<reflink idref="bib2" id="ref78">2</reflink>]) that the more positive the attitudes towards the behaviour, the stronger the person's intentions to do it. Yan et al. ([<reflink idref="bib49" id="ref79">49</reflink>]), in their systematic review, found that teachers' positive attitudes towards formative assessment strongly predicted their implementation intentions. In this study, alternative e‐assessment tasks were described as formative assessment in the survey according to the findings of a qualitative study on Hong Kong teachers' e‐assessment practices during school lockdowns (Zhan et al., [<reflink idref="bib54" id="ref80">54</reflink>]). Therefore, the finding could be deductively reasoned. However, the subject norms of using alternative e‐assessment did not significantly influence teachers' intentions. This finding aligns with the findings of Armitage and Conner ([<reflink idref="bib3" id="ref81">3</reflink>]). In their meta‐analysis review, they found that subjective norm was a weak predictor of intention. An explanation for this is that alternative assessment itself, whether online or offline, is a quite debated issue in Hong Kong because the use of such type of assessment tasks conflicts with the persistent use of public examinations for important decision‐making (Yan & Brown, [<reflink idref="bib47" id="ref82">47</reflink>]). The intense discussions may have muddled teachers' understanding of significant opinions about alternative e‐assessment, diminishing the impact of the subjective norms on their intentions.</p> <p>However, it was found that subject norms primarily predicted their intention of using e‐feedback, but attitudes did not. This finding contradicts Armitage and Conner's ([<reflink idref="bib3" id="ref83">3</reflink>]) finding that the subject norms weakly predicted peoples' behavioural intentions. This result should be interpreted considering feedback as a relational concept in the classroom (Dann, [<reflink idref="bib9" id="ref84">9</reflink>]). Feedback is a complex interactional process where others' reactions and appreciation of feedback can influence teachers' intention of doing e‐feedback practices. Meanwhile, this study found that teachers' attitudes did not significantly influence their intentions of using e‐feedback. Even though teachers have favourable attitudes towards feedback by recognising its benefits for learning and teaching, they may not have the desire or motivation to do it due to some contextual constraints such as big class sizes, heavy workloads and tight teaching schedules (Winstone & Carless, [<reflink idref="bib45" id="ref85">45</reflink>]).</p> <p>The findings of this study have implications for primary schools to successfully integrate technology into teachers' daily assessment practices. In this study, participants' intentions were identified as the strongest predictor of their e‐assessment. Perceived behavioural control was a significant predictor of their intentions no matter which type of e‐assessment was involved. Therefore, school administrators need to consider teachers' e‐assessment capacity building. Teachers need sustainable and hands‐on training instead of a one‐off and lecture‐based one. In the consecutive trainings, teachers are provided with the latest assessment apps., subject‐based e‐assessment examples and hands‐on opportunities.</p> <p>This study found that primary school teachers' intentions of using alternative e‐assessment and e‐feedback were weaker than those of using e‐tests/exercises. Interestingly, it was observed that teachers' attitudes significantly influenced their intentions to conduct alternative e‐assessment tasks, while the inclination to use e‐feedback was primarily driven by subject norms. This intriguing finding suggests that different strategies may be required to enhance teachers' intention of using these two types of e‐assessment. To enhance teachers' intentions of using e‐feedback, a whole school approach is suggested to create positive subject norms of using e‐feedback at the classroom level. School administrators need to build up a holistic e‐feedback environment and approaches by considering the existing e‐feedback practices, subject features, teachers' e‐feedback literacy and students' learning conditions. On the other hand, to increase teachers' intentions of using alternative e‐assessment tasks, their appreciation for the value of such e‐assessment should be encouraged. It may be difficult for primary school teachers to recognise the value of alternative e‐assessment tasks due to their habitual thinking and usual assessment practices in classrooms. Therefore, their pre‐existing conceptions of assessment should be understood and addressed via surveys and discussions. Additionally, it would be beneficial to establish a learning community where teachers can share their successful stories with alternative e‐assessment practices, along with its positive effects on learning. This exposure would help them understand the practical value and benefits of alternative e‐assessment for teaching and learning.</p> <p>In addition, the findings show that teachers' perceived behavioural control of e‐assessment (ie, e‐assessment literacy) significantly predicted their e‐assessment intentions and practices. In this study, the participants' perceived behavioural control of e‐assessment was not high. Schools must provide technical support and assessment resources to ensure teachers' mastery experiences of e‐assessment since mastery experiences have the most crucial impact on teachers' assessment confidence (Yan, [<reflink idref="bib46" id="ref86">46</reflink>]). Meanwhile, collaborative learning within schools is necessary. For example, teachers who teach different subjects and different grades can work together to share their good practices for using e‐assessment. Collaborative arrangements concerning e‐assessment in subject and year groups can increase the probability of sustained innovation and shared innovation across year groups and subjects (Huber & Helm, [<reflink idref="bib18" id="ref87">18</reflink>]). School administrators should support these professional learning communities by providing resources and guidance and making effective knowledge management of e‐assessment good practices.</p> <p>To conclude, the findings of the study have enhanced our understanding of primary school teachers' classroom‐based e‐assessment practices through the lens of the TPB, an area that has not been extensively explored through large‐scale investigation. Additionally, our research has contributed by categorising e‐assessment practices into three distinct types and identifying influential factors that impact teachers' decision‐making process when selecting different types of e‐assessment for their daily instruction. Unlike previous studies that generally examined teachers' intentions and practices of e‐assessment, our study offered a more comprehensive and detailed analysis. The study's findings revealed a significant relationship between teachers' intentions and their practices regarding specific e‐assessment. However, it was noted that the factors influencing their intentions to use alternative e‐assessments and e‐feedback varied. This notable discovery suggests the need for tailored strategies to enhance teachers' intentions in using different types of e‐assessment.</p> <p>Despite the significant findings, this study has some limitations which call for further studies. First, although the confirmative factor analysis supported the construct validity of the e‐assessment practice scale, the correlation between e‐feedback practices and alternative e‐assessment practices was relatively high. Such a high correlation may be caused by the natural connection between alternative assessment activities and feedback. Further research with a greater sample size should be conducted to examine whether alternative assessment activities and feedback should be integrated into a broad dimension. Second, teachers' e‐assessment practices were self‐reported and might not accurately represent the real practices in the classroom. Therefore, log data can be collected to triangulate teachers' self‐reports in the future study. Third, the inconsistency in the impact of teachers' intentions and perceived behavioural control of different types of teachers' e‐assessment practices were identified and interpreted. Qualitative data collection, such as interviews with teachers and school administrators and online unobtrusive observation of e‐assessment practices, is needed to gain an in‐depth understanding of the reasons causing inconsistent impacts. Finally, although the sample size is representative of Hong Kong primary school teachers, the findings should be cautiously interpreted in different contexts, especially in Western contexts where examination culture may not be as prevalent. In the future, a comparative study can be done between Western and Eastern classrooms to see if teachers from different cultural contexts have different intentions and practices of e‐assessment practices in their classrooms.</p> <hd id="AN0180170783-20">ACKNOWLEDGEMENTS</hd> <p>This study was supported by the Public Policy Research Funding Scheme (No.: 2021.A5.101.21D) from the Chief Executive's Policy Unit of the Government of the Hong Kong Special Administrative Region of the People's Republic of China.</p> <hd id="AN0180170783-21">CONFLICT OF INTEREST STATEMENT</hd> <p>No potential conflict of interest was reported by the authors.</p> <hd id="AN0180170783-22">DATA AVAILABILITY STATEMENT</hd> <p>The data that support the findings of this study can be accessed by contacting the corresponding author. 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Primary School Teachers' Classroom-Based E-Assessment Practices: Insights from the Theory of Planned Behaviour
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ying+Zhan%22">Ying Zhan</searchLink><br /><searchLink fieldCode="AR" term="%22Daner+Sun%22">Daner Sun</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9813-6306">0000-0002-9813-6306</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ho+Man+Kong%22">Ho Man Kong</searchLink><br /><searchLink fieldCode="AR" term="%22Ye+Zeng%22">Ye Zeng</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22British+Journal+of+Educational+Technology%22"><i>British Journal of Educational Technology</i></searchLink>. 2024 55(6):2740-2759.
– 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: 20
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Elementary+School+Teachers%22">Elementary School Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Evaluation%22">Student Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+Methods%22">Evaluation Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior+Theories%22">Behavior Theories</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Alternative+Assessment%22">Alternative Assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Attitudes%22">Teacher Attitudes</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Hong+Kong%22">Hong Kong</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/bjet.13478
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0007-1013<br />1467-8535
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: There is a global trend in the increased adoption of e-assessment in school classrooms to enhance learning. Teachers, as classroom-based assessment designers and implementers, play a vital role in such assessment change. However, little is known about school teachers' classroom-based e-assessment practices and the underlying reasons. To address this research gap, this study identified the factors influencing Hong Kong primary school teachers' e-assessment practices underpinned by the theory of planned behaviour (TPB). A large-scale survey was issued to 878 teachers via Qualtrics. Structural equation modelling (SEM) analysis shows that primary school teachers' intentions of using e-assessment and perceived behavioural control of it were the two strongest factors predicting their e-assessment practices in a general way. Specifically, teachers' intentions outweighed perceived behavioural control in determining their use of alternative e-assessment tasks and e-feedback, but this reversed for e-tests/exercises. The impact of perceived behavioural control was consistent across the three types of e-assessment practices. Furthermore, teachers' attitudes significantly influenced their intentions to use alternative e-assessment tasks, while subject norms primarily predicted their intentions to use e-feedback. The findings have implications for primary schools to take countermeasures to facilitate the successful implementation of e-assessment at the classroom level.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1443081
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1443081
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  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/bjet.13478
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 2740
    Subjects:
      – SubjectFull: Elementary School Teachers
        Type: general
      – SubjectFull: Student Evaluation
        Type: general
      – SubjectFull: Evaluation Methods
        Type: general
      – SubjectFull: Educational Technology
        Type: general
      – SubjectFull: Behavior Theories
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Intention
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      – SubjectFull: Predictor Variables
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      – SubjectFull: Alternative Assessment
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      – SubjectFull: Feedback (Response)
        Type: general
      – SubjectFull: Teacher Attitudes
        Type: general
      – SubjectFull: Hong Kong
        Type: general
    Titles:
      – TitleFull: Primary School Teachers' Classroom-Based E-Assessment Practices: Insights from the Theory of Planned Behaviour
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            NameFull: Ying Zhan
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              Y: 2024
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