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A Multi-Dimensional Scale for Measuring Undergraduates Interest in STEM Disciplines

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Title: A Multi-Dimensional Scale for Measuring Undergraduates Interest in STEM Disciplines
Language: English
Authors: Zubair Ahmad (ORCID 0000-0002-6606-2269), Almaas Sultana, Nitha Siby, Mohammad Ammar, Noora J. Al-Thani
Source: Journal of Science Education and Technology. 2025 34(4):611-620.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 10
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Undergraduate Students, Student Interests, Interest Inventories, STEM Education, Test Validity, Motivation, Self Efficacy, Self Concept, Occupational Aspiration, Test Reliability
DOI: 10.1007/s10956-024-10140-w
ISSN: 1059-0145
1573-1839
Abstract: One of the major challenges faced by the education system today is the lack of interest exhibited by undergraduates in Science, Technology, Engineering, and Mathematics (STEM) disciplines. This is particularly concerning as the world is becoming increasingly technology-driven, and a skilled workforce is necessary to meet future demands. Therefore, fostering interest among undergraduates in STEM fields is imperative to improve their engagement and persistence in these disciplines. Numerous initiatives have been undertaken to enhance students' STEM interests in formal, non-formal, and informal learning settings. However, assessing the effectiveness of these initiatives requires a robust and validated measurement tool grounded in theoretical and empirical evidence. Without a valid and reliable instrument, it would be challenging to determine the effectiveness of these initiatives in promoting STEM education and interest among undergraduates. This study presents a STEM Interest Scale (SIS) that captures diverse psychological factors that affect students' interest in STEM. To develop this scale, the study employs a cross-sectional quantitative design. The data collection process involved two phases for developing and validating the scale. In phase I, 280 participants were surveyed to perform exploratory factor analysis (EFA) to identify the underlying dimensions of STEM interest. In phase II, a sample of 266 students was used to assess the psychometric characteristics of the 'STEM Interest Scale (SIS) using confirmatory factor analysis (CFA) and nomological validity. The outcome of the EFA revealed that the STEM Interest scale is comprised of four psychological factors: intrinsic motivation, self-efficacy, self-concept, and employment aspiration, while the CFA and nomological network confirm the validity of these factors. The present research is a pioneering effort to holistically capture STEM interest, thereby paving the way for informed interventions in STEM education.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1477799
Database: ERIC
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  Value: <anid>AN0186780440;4n601aug.25;2025Jul23.05:04;v2.2.500</anid> <title id="AN0186780440-1">A Multi-Dimensional Scale for Measuring Undergraduates Interest in STEM Disciplines </title> <p>One of the major challenges faced by the education system today is the lack of interest exhibited by undergraduates in Science, Technology, Engineering, and Mathematics (STEM) disciplines. This is particularly concerning as the world is becoming increasingly technology-driven, and a skilled workforce is necessary to meet future demands. Therefore, fostering interest among undergraduates in STEM fields is imperative to improve their engagement and persistence in these disciplines. Numerous initiatives have been undertaken to enhance students' STEM interests in formal, non-formal, and informal learning settings. However, assessing the effectiveness of these initiatives requires a robust and validated measurement tool grounded in theoretical and empirical evidence. Without a valid and reliable instrument, it would be challenging to determine the effectiveness of these initiatives in promoting STEM education and interest among undergraduates. This study presents a STEM Interest Scale (SIS) that captures diverse psychological factors that affect students' interest in STEM. To develop this scale, the study employs a cross-sectional quantitative design. The data collection process involved two phases for developing and validating the scale. In phase I, 280 participants were surveyed to perform exploratory factor analysis (EFA) to identify the underlying dimensions of STEM interest. In phase II, a sample of 266 students was used to assess the psychometric characteristics of the 'STEM Interest Scale (SIS) using confirmatory factor analysis (CFA) and nomological validity. The outcome of the EFA revealed that the STEM Interest scale is comprised of four psychological factors: intrinsic motivation, self-efficacy, self-concept, and employment aspiration, while the CFA and nomological network confirm the validity of these factors. The present research is a pioneering effort to holistically capture STEM interest, thereby paving the way for informed interventions in STEM education.</p> <p>Keywords: STEM Interest; Intrinsic motivation; Self-concept; Self-efficacy; Employment aspiration; Scale validation; Education Specialist Studies In Education Psychology and Cognitive Sciences Psychology</p> <p>Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s10956-024-10140-w.</p> <hd id="AN0186780440-2">Introduction</hd> <p>Science, Technology, Engineering, and Mathematics (STEM) skills play a vital role in promoting innovation, economic growth, and societal well-being (Sellami et al., [<reflink idref="bib42" id="ref1">42</reflink>]; Vulperhorst et al., [<reflink idref="bib48" id="ref2">48</reflink>]). Despite the growing importance of STEM education, there has been a decline in the number of students graduating from STEM disciplines (Ahmad et al., [<reflink idref="bib1" id="ref3">1</reflink>]; Dagley et al., [<reflink idref="bib11" id="ref4">11</reflink>]). One of the major causes of this decline is the lack of interest among students in STEM courses (Lytle & Shin, [<reflink idref="bib29" id="ref5">29</reflink>]). Hence, it is essential to comprehend the factors contributing to students' disinterest in STEM disciplines (Maltese et al., [<reflink idref="bib32" id="ref6">32</reflink>]), using a validated scale encompassing all potential dimensions of interest. This can aid in understanding the underlying reasons behind their lack of interest in STEM disciplines.</p> <p>While various STEM scales exist, they lack comprehensiveness and fail to capture the multifaceted nature of STEM interest (refer to Table 1). Existing scales focus on specific domains and overlook holistic aspects of STEM interest (Staus et al., [<reflink idref="bib43" id="ref7">43</reflink>]; Tyler-Wood et al., [<reflink idref="bib44" id="ref8">44</reflink>]; Unfried et al., [<reflink idref="bib45" id="ref9">45</reflink>]). The existing scales claiming to measure STEM interest are designed for students and measure interest primarily from a career perspective. However, there is a noticeable absence of such scales tailored explicitly for students that consider psychological aspects of interest. In order to better understand and assess interest in the fields of science, technology, engineering, and mathematics (STEM), there is a need for a comprehensive and unified tool that can effectively measure STEM interest across various dimensions. The present tool would enable educators, researchers, and policymakers to gain valuable insights into the factors that influence STEM interest and help foster greater engagement in these critical fields. The present study addresses the gap by developing and validating a robust STEM Interest Scale. The proposed scale encompasses various dimensions of STEM interest, which have been derived from self-determination theory, social cognitive theory, social cognitive career theory, and person-centered theory. By developing a comprehensive STEM Interest Scale, this study seeks to facilitate the identification of patterns, trends, and potential areas for intervention to enhance STEM engagement. Ultimately, the validated scale can contribute to promoting sustained interest and participation of students in STEM fields.</p> <p>Table 1 An overview of various measures for STEM published in literature during the last decade and their descriptions</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Measures</p></th><th align="left"><p>Source/citation</p></th><th align="left"><p>Sample/target population</p></th><th align="left"><p>Methodology</p></th><th align="left"><p>Description</p></th></tr></thead><tbody><tr><td align="left"><p>STEM Interest Scale</p></td><td align="left"><p>Staus et al., (<xref ref-type="bibr" rid="bibr43">2020</xref>)</p></td><td align="left"><p>Adolescents of Grade 6th, 7th and 8th at schools in USA</p></td><td align="left"><p>Quantitative method (Multiple indicators, multiple causes approach)</p></td><td align="left"><p>The scale measures STEM interest by concentrating solely on STEM content</p></td></tr><tr><td align="left"><p>Bitara-STEM</p></td><td align="left"><p>Mohd Shahali et al., (<xref ref-type="bibr" rid="bibr33">2019</xref>)</p></td><td align="left"><p>Middle school students in Malaysia</p></td><td align="left"><p>Mixed method, (ANOVA and Thematics analysis)</p></td><td align="left"><p>This survey only measures the STEM interest from a career perspective</p></td></tr><tr><td align="left"><p>MATS Scale</p></td><td align="left"><p>Hillman et al., (<xref ref-type="bibr" rid="bibr20">2016</xref>)</p></td><td align="left"><p>Elementary, Middle, and High school students in the USA</p></td><td align="left"><p>Mixed method (inter-rater agreement and Cronbach's alpha co-efficient)</p></td><td align="left"><p>The survey assesses students' attitudes towards science across four subscales: attitudes towards school science, desire to become a scientist, the value of scientists to society, and perceptions of scientists</p></td></tr><tr><td align="left"><p>STEM Career Interest Survey</p></td><td align="left"><p>Kier et al., (<xref ref-type="bibr" rid="bibr24">2014</xref>)</p></td><td align="left"><p>Middle school students of grade 6th, 7th, and 8th in USA</p></td><td align="left"><p>Quantitative (confirmatory factor analysis)</p></td><td align="left"><p>Emphasis on career aspects</p></td></tr><tr><td align="left"><p>STEM Scale</p></td><td align="left"><p>Oh et al., (<xref ref-type="bibr" rid="bibr36">2013</xref>)</p></td><td align="left"><p>High school students in the USA</p></td><td align="left"><p>Quantitative Method (descriptive statistics and exploratory factor analysis)</p></td><td align="left"><p>It measures overall educational and career interests</p></td></tr><tr><td align="left"><p>STEM Semantics Survey</p></td><td align="left"><p>Tyler-Wood (<xref ref-type="bibr" rid="bibr44">2010</xref>)</p></td><td align="left"><p>Middle school teachers and their students in Alaska, Hawaii, Louisiana, Maine, Texas, and Vermont</p></td><td align="left"><p>Quantitative (exploratory factor analysis)</p></td><td align="left"><p>It primarily focused on career aspects</p></td></tr></tbody></table> </ephtml> </p> <p>Source: Authors Compilation</p> <hd id="AN0186780440-3">Literature Review</hd> <p>Interest plays a vital role in an individual's affective functioning with respect to learning (Bandura, [<reflink idref="bib6" id="ref10">6</reflink>]). It is a multifaceted and complex motivational construct (Dierks et al., [<reflink idref="bib13" id="ref11">13</reflink>]; Hazari et al., [<reflink idref="bib17" id="ref12">17</reflink>]). In the present context, STEM Interest is operationalized as an individual's motivation, determination, self-assurance, and sense of self-belonging in their engagement within STEM fields. These factors significantly influence students' persistence (Allen & Robbins, [<reflink idref="bib3" id="ref13">3</reflink>]), attention (Hidi & Renninger, [<reflink idref="bib19" id="ref14">19</reflink>]), and enrollment in higher education STEM programs (Mohd Shahali et al., [<reflink idref="bib33" id="ref15">33</reflink>]; Vulperhorst et al., [<reflink idref="bib48" id="ref16">48</reflink>]), emphasizing the need for a valid and reliable instrument to measure it effectively. However, the existing literature (Table 1) on STEM interest reveals a scarcity of studies with a comprehensive, multifaceted scale, leading to a gap in the literature.</p> <p>The multifaceted nature of an interest in STEM can be well predicted based on motivational theories (Murphy et al., [<reflink idref="bib34" id="ref17">34</reflink>]). The theoretical framework of the present study is anchored on four main theories that explain the factors influencing students' interest in STEM disciplines: self-determination theory, social cognitive theory, person-centered theory, and social cognitive career theory. These theories offer a comprehensive framework for analyzing STEM interest as a multidimensional concept that includes self-efficacy, self-concept, intrinsic motivation, and employment aspiration. According to self-determination theory, intrinsic motivation is essential for maintaining sustained interest in STEM subjects (Deci & Ryan, [<reflink idref="bib12" id="ref18">12</reflink>]). The social cognitive theory states that self-efficacy, or students' belief in their ability to perform well in STEM tasks, influences their engagement, effort, persistence, and achievement outcomes (Bandura, [<reflink idref="bib5" id="ref19">5</reflink>], [<reflink idref="bib7" id="ref20">7</reflink>]). Person-centered theory claims that self-concept, or students' perception of themselves within the STEM context, shapes their interest and outcomes associated with STEM (Rogers, [<reflink idref="bib38" id="ref21">38</reflink>]). Finally, social cognitive career theory suggests that employment aspiration, or students' career-related goals, also significantly affects STEM interest and enrollment (Lent et al., [<reflink idref="bib25" id="ref22">25</reflink>]). The following sections will elaborate on the theories and factors that have been proposed.</p> <p>Self-determination theory, a widely recognized psychological theory, emphasizes the significance of intrinsic motivation in sustaining interest and engagement in STEM subjects (Deci & Ryan, [<reflink idref="bib12" id="ref23">12</reflink>]). Intrinsic motivation, which refers to an individual's inherent drive and enjoyment of a task or activity, is crucial in nurturing interest and passion in STEM domains (Hidi & Renninger, [<reflink idref="bib19" id="ref24">19</reflink>]; Zaharin et al., [<reflink idref="bib52" id="ref25">52</reflink>]). Research has shown that intrinsic motivation has a positive impact on academic success, as it is strongly associated with students' interest in STEM subjects and careers (Maltese & Tai, [<reflink idref="bib31" id="ref26">31</reflink>]; Wang & Degol, [<reflink idref="bib49" id="ref27">49</reflink>]). Therefore, fostering intrinsic motivation among students is essential for promoting their engagement and success in STEM fields.</p> <p>Bandura's Social Cognitive Theory proposes that a person's self-efficacy plays a significant role in determining the level of effort that an individual puts forth to succeed in STEM-related tasks (Bandura, [<reflink idref="bib5" id="ref28">5</reflink>]; Schunk & DiBenedetto, [<reflink idref="bib40" id="ref29">40</reflink>]). In this context, self-efficacy refers to the belief that students hold about their abilities to perform well in STEM tasks. This belief is known to strongly influence their engagement, effort, persistence, and achievement outcomes (Franks & Capraro, [<reflink idref="bib15" id="ref30">15</reflink>]; Honicke et al., [<reflink idref="bib23" id="ref31">23</reflink>]). Therefore, it is important for educators to focus on building students' self-efficacy in STEM subjects, as it is a crucial factor in developing their interest and motivation to succeed.</p> <p>Carl Rogers, the renowned psychologist, proposed the person-centered theory, which suggests that a student's self-concept within the STEM context is critical in shaping their interest and outcomes associated with STEM. Self-concept refers to a student's perception of their abilities and competence in STEM and is a significant predictor of their interest in STEM fields. Research studies have shown that there is a strong relationship between self-concept and STEM outcomes, and it is an essential factor in determining students' success in STEM education. Although self-efficacy and self-concept are related, they are distinct concepts that contribute uniquely to STEM interests. While self-efficacy is concerned with a student's belief in their ability to complete a task successfully, self-concept refers to their general perception of themselves in a particular domain, such as STEM. It is vital to note that both self-efficacy and self-concept are critical in increasing students' interest in STEM and can play a significant role in shaping their future careers.</p> <p>The Social Cognitive Career Theory (SCCT) proposed by Lent et al., in [<reflink idref="bib25" id="ref32">25</reflink>] provides a framework for understanding how students' employment aspirations directly influence their interest in STEM fields. This theory is essential in assessing students' motivation, beliefs, and future aspirations within the STEM landscape. According to recent research, employment aspirations or career-related goals significantly shape students' interest and enrollment in STEM fields (Ahmed & Mudrey, [<reflink idref="bib2" id="ref33">2</reflink>]; Luo et al., [<reflink idref="bib28" id="ref34">28</reflink>]). Notably, a student's employment aspiration is influenced by their interests, values, and available opportunities. Studies have shown that students with high employment aspirations tend to have greater motivation to pursue STEM professions (Maltese & Tai, [<reflink idref="bib30" id="ref35">30</reflink>]; Wang et al., [<reflink idref="bib50" id="ref36">50</reflink>]). Therefore, it is crucial to consider students' career-related goals while designing STEM education programs to foster their interest and engagement in STEM fields. By doing so, we can help students develop a passion for STEM and prepare them for successful careers in the future.</p> <p>Therefore, based on the insights from the above-mentioned theories, the study theorizes that STEM interest is inherently a multidimensional construct. The proposed framework acknowledges the interplay of intrinsic motivation, self-concept, self-efficacy, and employment aspiration in shaping students' STEM interests. Therefore, by integrating these theories, the study aims to develop and validate a robust and comprehensive instrument for measuring STEM interest among undergraduate students. This premise prompts the formulation of the following Research Questions (RQ).</p> <p>RQ 1 Are intrinsic motivation, self-efficacy, self-concept, and employment aspirations dimensions of the proposed STEM Interest Scale?</p> <p>RQ 2: To what extent does a multi-dimensional "STEM Interest" scale demonstrate reliability and validity in measuring STEM interest among undergraduate students?</p> <hd id="AN0186780440-4">Methodology</hd> <p>The current study utilized well-established scale development methodologies following a structured approach established in the literature (Churchill, [<reflink idref="bib9" id="ref37">9</reflink>]; Hinkin, [<reflink idref="bib21" id="ref38">21</reflink>]). The scale validity process consists of three distinct stages.</p> <hd id="AN0186780440-5">Stage 1</hd> <p>First, we developed items to measure STEM interest using the PRISMA methodology that resulted in the generation of items (see Table S1). The items' content validity was established through the Delphi study. First, the invitations were extended to ten experts, of whom eight agreed to participate. These subject experts were professors specializing in STEM education. The experts were informed that the scale would measure the STEM interests of undergraduates and were provided with the definition of STEM interests. They were asked to critically assess each statement for comprehensiveness, wording, and relevance using a 3-point scale, as suggested by (Zaichkowsky ([<reflink idref="bib53" id="ref39">53</reflink>]). The draft items were presented to the experts, who individually scored each item as not representative (<reflink idref="bib1" id="ref40">1</reflink>), somewhat representative (<reflink idref="bib2" id="ref41">2</reflink>), or clearly representative (<reflink idref="bib3" id="ref42">3</reflink>), following the suggested guidelines (Lin & Hsieh, [<reflink idref="bib26" id="ref43">26</reflink>]).</p> <hd id="AN0186780440-6">Stage 2</hd> <p>The refinement stage of the scale employed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) on the proposed scale. The data collected during phase I underwent exploratory factor analysis (EFA), while the data gathered in phase II involved performing confirmatory factor analysis (CFA) and nomological validity. This approach is consistent with the scale purification protocols established by Churchill ([<reflink idref="bib9" id="ref44">9</reflink>]) and Hinkin ([<reflink idref="bib21" id="ref45">21</reflink>]) and further supported by Schwarz ([<reflink idref="bib41" id="ref46">41</reflink>]). Using a purposive sampling technique, we collected responses from undergraduates enrolled in STEM courses at University A (Table 2). Participants were thoroughly briefed on the study's objectives and procedures, and their consent was obtained. The participation of students in the survey was voluntary, with confidentiality guaranteed for research purposes. The survey instrument used was approved by the University A Institutional Review Board (XX-IRB) with the approval number XX-IRB 1721-EA/22. The questionnaire was comprised of two sections: the first gathered demographic details such as gender, age, and ethnicity, while the second contained statements regarding STEM interests. The survey was administered in two phases via Google Forms.</p> <p>Table 2 Demographic details of undergraduate participants considered for STEM Interest (<emph>N</emph> = 546)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p><bold>Variables</bold></p></th><th align="left"><p><bold>Parameters</bold></p></th><th align="left"><p><bold><italic>N</italic></bold></p></th><th align="left"><p><bold>%</bold></p></th></tr></thead><tbody><tr><td align="left" rowspan="4"><p><bold><italic>Age</italic></bold></p></td><td align="left"><p>Under 18</p></td><td align="left"><p>11</p></td><td align="left"><p>2</p></td></tr><tr><td align="left"><p>19 years to 21 years</p></td><td align="left"><p>296</p></td><td align="left"><p>54.21</p></td></tr><tr><td align="left"><p>22 years to 25 years</p></td><td align="left"><p>211</p></td><td align="left"><p>38.64</p></td></tr><tr><td align="left"><p>Over 25 years</p></td><td align="left"><p>28</p></td><td align="left"><p>5.1</p></td></tr><tr><td align="left" rowspan="2"><p><bold><italic>Gender</italic></bold></p></td><td align="left"><p>Male</p></td><td align="left"><p>215</p></td><td align="left"><p>39.37</p></td></tr><tr><td align="left"><p>Female</p></td><td align="left"><p>331</p></td><td align="left"><p>60.62</p></td></tr><tr><td align="left" rowspan="2"><p><bold>Ethnicity</bold></p></td><td align="left"><p>National</p></td><td align="left"><p>159</p></td><td align="left"><p>29.12</p></td></tr><tr><td align="left"><p>Expatriates</p></td><td align="left"><p>387</p></td><td align="left"><p>70.87</p></td></tr></tbody></table> </ephtml> </p> <p>A purposive sampling technique was used to collect the data. The data were run through SPSS version 29 for exploratory factor analysis using varimax rotation and then the extracted factors were confirmed using confirmatory factors analysis through AMOS version 29 to ensure their robustness.</p> <hd id="AN0186780440-7">Stage 3</hd> <p>After the confirmation of the factors, we assessed the scale's reliability and validity by using various criteria such as Cronbach's alpha, composite reliability (CR), average variance extracted (AVE), common method bias, and nomological validity. The comprehensive evaluation ensures the scale's suitability for capturing STEM interest effectively.</p> <hd id="AN0186780440-8">Results</hd> <p></p> <hd id="AN0186780440-9">Stage 1: Item Generation and Selection</hd> <p>First, a systematic literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Methodology (Fig. 1), with data sourced exclusively from SCOPUS. Our search query was structured as follows: (("STEM Interest" OR "Interest in STEM") AND ("Engagement" OR "Motivation") AND ("scale" OR "measurement" OR "instrument" OR "questionnaire" OR "survey")). The search included only English-language articles where the search query was found in the title, abstract, or keywords. This review resulted in the selection of 30 articles to create STEM interest items. Following the deductive approach as proposed by Hinkin ([<reflink idref="bib21" id="ref47">21</reflink>]), an initial pool of 25 items was generated for the proposed measure in the Likert Scale. These items were evaluated using a 5-point Likert scale ranging from 5—strongly agree to -strongly disagree (Nemoto & Beglar, [<reflink idref="bib35" id="ref48">35</reflink>]).</p> <p>Graph: Fig. 1 PRISMA flowchart of the literature search and selection process for identifying studies on students' interest in STEM</p> <p>During the preliminary screening, experts recommended removing and modifying certain items due to issues such as item overlap and ambiguous formulation. Only items rated clearly or somewhat representative were retained. Consequently, based on their feedback, some items were revised, and some were eliminated. This resulted in a set of 23 items out of the original 25.</p> <p>The revised scale with 23 items was then resubmitted to the experts for further evaluation. They were asked to rate the items based on their relevancy, indicating whether they were not relevant, somewhat relevant, or highly relevant. Subsequently, the content validity ratio (CVR) was calculated for each item using the formula suggested by Veneziano and Hooper ([<reflink idref="bib47" id="ref49">47</reflink>]) as given in Eq. (<reflink idref="bib1" id="ref50">1</reflink>).</p> <p>1 <ephtml> <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mtext>CVR</mtext><mo>=</mo><mfenced close=")" open="("><mi>N</mi><mi>e</mi><mo>-</mo><mfrac><mi>N</mi><mn>2</mn></mfrac></mfenced><mo>÷</mo><mfenced close=")" open="("><mfrac><mi>N</mi><mn>2</mn></mfrac></mfenced></mrow></math> </ephtml></p> <p>Graph</p> <p>where, <emph>Ne</emph> = Number of experts rated highly relevant, and <emph>N</emph> = Total Number of experts participating in content validity. The content validity ratio was calculated, resulting in the deletion of 3 items with a CVR value of less than 0.75 removed from the scale. As a result, the scale was now comprised of 20 items that underwent the next stage of scale refinement.</p> <hd id="AN0186780440-10">Stage 2: Refinement of Scale</hd> <p>In phase I, 800 questionnaires were disseminated, yielding 297 responses. Following scrutiny for seriousness and completeness, 17 questionnaires were excluded, resulting in 280 valid responses and a response rate of 35%. Phase II of data collection involved the distribution of 500 questionnaires, with 275 returned. After excluding nine questionnaires with non-serious responses, 266 responses were considered suitable, achieving a response rate of 53.6%. Adhering to the recommendations of Hair et al., ([<reflink idref="bib16" id="ref51">16</reflink>]), our dataset maintained a 3:1 ratio of cases to variables, ensuring its appropriateness to proceed with factor analysis.</p> <hd id="AN0186780440-11">Exploratory Factor Analysis (EFA)</hd> <p>The data collected on a 20-item scale underwent factor analysis. Before employing EFA first, the appropriateness of data was evaluated using the Kaiser–Meyer–Olkin (KMO) coefficient and Bartlett's sphericity test. The KMO value exceeded the specified threshold, indicating adequate sampling adequacy (Table 3). Employing Varimax rotation and principal components analysis, the exploratory factor analysis achieved convergence after 25 iterations, explaining 55.7% of the total variance. Four factors with eigenvalues exceeding 1.0 were identified, as detailed in Table 4. By following the established criteria, items with factor loadings below 0.40 were eliminated, resulting in the removal of five items to ensure scale robustness. The overall commonalities were determined to be moderate to strong, aligning with previous research. The study maintained a four-factor solution, categorizing statements under the dimensions of intrinsic motivation, self-concept, self-efficacy, and employment aspiration.</p> <p>Table 3 Kaiser–Meyer–Olkin test for sample adequacy of STEM Interest Scale for undergraduates</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" colspan="2"><p>KMO and Bartlett's test</p></th></tr><tr><th align="left"><p>Kaiser–Meyer–Olkin measure of sampling adequacy</p></th><th align="left"><p>0.830</p></th></tr></thead><tbody><tr><td align="left"><p>Bartlett's test of sphericity approx.chi-square</p></td><td char="." align="char"><p>1944.90</p></td></tr><tr><td align="left"><p>df</p></td><td char="." align="char"><p>105.0</p></td></tr><tr><td align="left"><p>Sig</p></td><td char="." align="char"><p> < 0.001</p></td></tr></tbody></table> </ephtml> </p> <p>Table 4 Summary of items, factor loading, and factors that emerged in exploratory factor analysis of the STEM Interest Scale (SIS)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p><bold>Factor extracted</bold></p></th><th align="left"><p><bold>Item code</bold></p></th><th align="left"><p><bold>Items</bold></p></th><th align="left"><p><bold>Factor loading</bold></p></th></tr></thead><tbody><tr><td align="left" rowspan="5"><p>Employment aspiration</p></td><td align="left"><p>EA01</p></td><td align="left"><p>I look forward to improving my skills to improve my chances of employment</p></td><td char="." align="char"><p>0.680</p></td></tr><tr><td align="left"><p>EA02</p></td><td align="left"><p>I am aware of the career positions in which I want to work</p></td><td char="." align="char"><p>0.658</p></td></tr><tr><td align="left"><p>EA03</p></td><td align="left"><p>I complete tasks and assignments on time</p></td><td char="." align="char"><p>0.609</p></td></tr><tr><td align="left"><p>EA04</p></td><td align="left"><p>I would like to be employed after my graduation</p></td><td char="." align="char"><p>0.591</p></td></tr><tr><td align="left"><p>EA05</p></td><td align="left"><p>I am willing to work as hard as possible on tasks assigned to me in my job</p></td><td char="." align="char"><p>0.545</p></td></tr><tr><td align="left" rowspan="5"><p>Self-Efficacy</p></td><td align="left"><p>SE01</p></td><td align="left"><p>I can quickly solve problems that are analytical and scientific</p></td><td char="." align="char"><p>0.716</p></td></tr><tr><td align="left"><p>SE02</p></td><td align="left"><p>I always think of possible alternatives</p></td><td char="." align="char"><p>0.656</p></td></tr><tr><td align="left"><p>SE03</p></td><td align="left"><p>I always question things heard or read in class to improve my knowledge</p></td><td char="." align="char"><p>0.648</p></td></tr><tr><td align="left"><p>SE04</p></td><td align="left"><p>I am willing to do extra work on tasks to improve my knowledge</p></td><td char="." align="char"><p>0.600</p></td></tr><tr><td align="left"><p>SE05</p></td><td align="left"><p>I concentrate as hard as possible when doing a task</p></td><td char="." align="char"><p>0.469</p></td></tr><tr><td align="left" rowspan="3"><p>Self-concept</p></td><td align="left"><p>SC01</p></td><td align="left"><p>I am confident in attending conferences/events when I need to engage in presenting academic/research work</p></td><td char="." align="char"><p>0.817</p></td></tr><tr><td align="left"><p>SC02</p></td><td align="left"><p>I am confident of meeting new people to improve my academic life</p></td><td char="." align="char"><p>0.800</p></td></tr><tr><td align="left"><p>SC03</p></td><td align="left"><p>I am confident in communicating with new people to improve my understanding of any of the academic/research-related topics</p></td><td char="." align="char"><p>0.797</p></td></tr><tr><td align="left" rowspan="2"><p>Intrinsic Motivation</p></td><td align="left"><p>IM01</p></td><td align="left"><p>I practice my course lessons after class to improve my GPA scores</p></td><td char="." align="char"><p>0.810</p></td></tr><tr><td align="left"><p>IM02</p></td><td align="left"><p>I constantly update myself on the course lessons before attending the lessons</p></td><td char="." align="char"><p>0.801</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0186780440-12">Confirmatory Factor Analysis (CFA)</hd> <p>CFA was performed on the STEM Interest Scale using data collected during phase II. Initially, the model fit appeared satisfactory, but upon closer examination, an item (EA03) was deemed unsuitable due to its low factor loading (0.37); hence, subjective judgment, supported by input from a subject expert, guided the decision to remove the item (EA03). After removing item no. EA03, we conducted another CFA, which showed a significant decrease in the chi-square value in Model II, from 212.88 in the initial model to 173.00. This reinforces the validity of our factor structure, which demonstrated a good model fit, as indicated in Table 5 (CFA default model II). The values of RMR, GFI, AGFI, CFI, and RMSEA, met the threshold criteria suggested by Fornell and Larker ([<reflink idref="bib14" id="ref52">14</reflink>]), thereby reinforcing the validity of the theoretical model. Schumacker and Lomax ([<reflink idref="bib39" id="ref53">39</reflink>]) suggest that when most fit indices meet or exceed these thresholds, it is reasonable to infer that the data support the theoretical model. Therefore, the standard fit indices confirm the validity of the factor structure of the model.</p> <p>Table 5 Model fit indices of confirmatory factor analysis for STEM Interest Scale</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>CFA default model</p></th><th align="left"><p>RMR</p></th><th align="left"><p>GFI</p></th><th align="left"><p>AGFI</p></th><th align="left"><p>CFI</p></th><th align="left"><p>RMSEA</p></th><th align="left"><p><italic>χ</italic>2</p></th><th align="left"><p>Df</p></th><th align="left"><p><italic>p</italic> value</p></th><th align="left"><p><italic>χ</italic>2/df</p></th></tr></thead><tbody><tr><td align="left"><p>I (with EA03)</p></td><td align="left"><p>0.044</p></td><td align="left"><p>0.952</p></td><td align="left"><p>0.933</p></td><td align="left"><p>0.932</p></td><td align="left"><p>0.052</p></td><td align="left"><p>212.88</p></td><td align="left"><p>86</p></td><td align="left"><p>.000</p></td><td align="left"><p>2.475</p></td></tr><tr><td align="left"><p>II (without EA03)</p></td><td align="left"><p>0.044</p></td><td align="left"><p>0.957</p></td><td align="left"><p>0.939</p></td><td align="left"><p>0.944</p></td><td align="left"><p>0.050</p></td><td align="left"><p>173.00</p></td><td align="left"><p>73</p></td><td align="left"><p>.000</p></td><td align="left"><p>2.370</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0186780440-13">Stage 3: Scale Evaluation</hd> <p></p> <hd id="AN0186780440-14">Multidimensionality and Reliability</hd> <p>The application of CFA in the previous step illuminated the multi-dimensionality of the construct, providing a favorable indication to proceed with the reliability analysis of the scale. Composite reliability (CR) and Cronbach's alpha coefficient were used to examine the internal consistency. Across the sub-dimensions of the scale, Cronbach's alpha values ranged from 0.680 to 0.758 (refer to Table 6). Moreover, the STEM Interest Scale displayed composite reliability with CR = 0.803, further validating the scale (Cronbach, [<reflink idref="bib10" id="ref54">10</reflink>]). Therefore, it can be implicit that the STEM Interest Scale demonstrates a significant level of convergence. The current scale exhibits robust construct reliability, consistent with the criteria delineated by Fornell and Larcker ([<reflink idref="bib14" id="ref55">14</reflink>]).</p> <p>Table 6 Reliability statistics for dimensions of STEM Interest Scale</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>S.no</p></th><th align="left"><p>Sub-dimension</p></th><th align="left"><p>No. of items</p></th><th align="left"><p>Cronbach's alpha</p></th></tr></thead><tbody><tr><td align="left"><p>1</p></td><td align="left"><p>Intrinsic motivation</p></td><td align="left"><p>2</p></td><td char="." align="char"><p>0.680</p></td></tr><tr><td align="left"><p>2</p></td><td align="left"><p>Self-efficacy</p></td><td align="left"><p>5</p></td><td char="." align="char"><p>0.722</p></td></tr><tr><td align="left"><p>3</p></td><td align="left"><p>Self-Concept</p></td><td align="left"><p>3</p></td><td char="." align="char"><p>0.758</p></td></tr><tr><td align="left"><p>4</p></td><td align="left"><p>Employment Aspiration</p></td><td align="left"><p>4</p></td><td char="." align="char"><p>0.682</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0186780440-15">Construct Validity of STEM Interest Scale</hd> <p>The construct validity of the present scale was assessed with average variance extracted (AVE) and composite reliability (CR) as per the suggestion given by Fornell and Larcker ([<reflink idref="bib14" id="ref56">14</reflink>]). The average variance extracted (AVE) was found to be 0.506, and the composite reliability of the scale was found to be 0.803, which is up to the threshold value. The present scale ensures convergent validity as composite reliability (CR) > average variance extracted (AVE) > 0.5.</p> <hd id="AN0186780440-16">Common Method Bias</hd> <p>Harman's single-factor matrix was employed to assess common method variance, as recommended by Aulakh and Gencturk ([<reflink idref="bib4" id="ref57">4</reflink>]). The exploratory factor analysis (EFA) outcomes revealed that none of the four factors accounted for more than 50% of the variance. Consequently, the study did not exhibit common method bias, as per the suggestion of Peng et al., ([<reflink idref="bib37" id="ref58">37</reflink>]).</p> <hd id="AN0186780440-17">Nomological Validity</hd> <p>In the present research, the nomological validity of the proposed scale was established with the 'intention to drop out' (Fig. 2). We employed a two-item scale adapted from Xu and Webber ([<reflink idref="bib51" id="ref59">51</reflink>]) to measure the intention to drop. The data was collected in phase II using a five-point Likert scale to confirm the strength of the nomological network. The collected data were analyzed using AMOS 29. The findings indicate that there exists a negative correlation between STEM Interest and intention to drop out (Fig. 2). The structural model illustrates the relationships between dimensions of STEM interest and their impact on the intent to drop out from STEM courses. The path coefficients indicate the strength and direction of these relationships.</p> <p>The existing body of literature anticipates diverse consequences of STEM interest, including STEM stereotypes (Luo & So, [<reflink idref="bib27" id="ref60">27</reflink>]; Luo et al., [<reflink idref="bib28" id="ref61">28</reflink>]), STEM Learning experience (Chachashvili-Bolotin et al., [<reflink idref="bib8" id="ref62">8</reflink>]), and intent to drop out (van den Hurk et al., [<reflink idref="bib46" id="ref63">46</reflink>]). Therefore, the finding aligns with the outcome of nomological validity.</p> <p>Graph: Fig. 2 Structural Equation Model to assess the nomological validity of STEM Interest with Intent to Dropout</p> <p>The psychometric characteristics of the construct used to form a nomological network were assessed, revealing reliability coefficients of 0.798 for STEM Interest and 0.711 for intent to leave. This model (Fig. 2) was evaluated using average variance extracted (AVE), Composite Reliability, and discriminant validity following the guidelines of Fornell and Larcker ([<reflink idref="bib14" id="ref64">14</reflink>]). Table 7 displays the average variance extracted (AVE), composite reliability (CR), maximum shared squared variance (MSV), and average shared squared variance (ASV) for both the intent to drop and STEM Interest constructs. The results show that CR > AVE > 0.5 indicates a high level of convergent validity within the model. To ensure discriminant validity, the Heterotrait-Monotrait ratio of correlations (HTMT) criteria (displayed in Table 8) was applied, with an acceptable value below 0.90 (Henseler et al., [<reflink idref="bib18" id="ref65">18</reflink>]). The findings of structural equation modeling revealed a favorable fit for the model (RMSEA = 0.046, GFI = 0.949, AGFI = 0.932, CFI = 0.941, <emph>χ</emph>2 = 242.67, <emph>χ</emph>2/df = 2.129), no adjustments were made to the model fit due to its predetermined relationships. The standard estimates for the path STEM Interest → Intent to dropout were − 0.17, signifying significance at the 1% level, suggesting a negative correlation. It can be concluded that having an interest in STEM predicts persistence in the field, as measured through intent to dropout rates, thus verifying the validity of the scale.</p> <p>Table 7 Summary of convergent validity of STEM Interest Scale and intention to dropout</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>CR</p></th><th align="left"><p>AVE</p></th><th align="left"><p>MSV</p></th><th align="left"><p>STEM interest</p></th><th align="left"><p>Intent to drop out</p></th></tr></thead><tbody><tr><td align="left"><p>STEM Interest</p></td><td char="." align="char"><p>0.793</p></td><td char="." align="char"><p>0.534</p></td><td char="." align="char"><p>0.031</p></td><td char="." align="char"><p><bold>0.731</bold></p></td><td char="." align="char"><p>–</p></td></tr><tr><td align="left"><p>Intent to drop out</p></td><td char="." align="char"><p>0.714</p></td><td char="." align="char"><p>0.556</p></td><td char="." align="char"><p>0.031</p></td><td char="." align="char"><p>−0.175**</p></td><td char="." align="char"><p><bold>0.746</bold></p></td></tr></tbody></table> </ephtml> </p> <p>Table 8 Heterotrait-Monotrait ratio to assess discriminant validity of STEM Interest Scale</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>STEM</p></th><th align="left"><p>Dropout</p></th></tr></thead><tbody><tr><td align="left"><p>STEM</p></td><td char="." align="char" /><td align="left"><p>–</p></td></tr><tr><td align="left"><p>DROPOUT</p></td><td char="." align="char"><p>0.200</p></td><td align="left" /></tr></tbody></table> </ephtml> </p> <p>The HTMT ratio values of the above table highlight the correlations between the construct where an HTMT value less than 0.85 indicates discriminant validity</p> <hd id="AN0186780440-18">Discussion</hd> <p>The discourse on STEM interest within scholarly literature has predominantly focused on career-related or content-specific aspects, often viewing interest through an outcome lens, such as career prospects. However, existing scales purportedly measuring STEM interest lack robust support for construct validity, with their psychometric properties typically tested solely through exploratory factor analysis (EFA). For instance, the Bitara-STEM scale (Mohd Shahali et al., [<reflink idref="bib33" id="ref66">33</reflink>]) and the STEM semantics survey developed by Tyler-Wood, Knezek, and Christensen (Tyler-Wood et al., ([<reflink idref="bib44" id="ref67">44</reflink>]), both employed EFA and primarily assessed learners' interest in STEM-related careers or perceptions of STEM disciplines among middle school students.</p> <p>Addressing these limitations, the present research endeavors to develop and validate a comprehensive instrument to measure STEM interest by adopting an established scale development procedure (Hinkin, [<reflink idref="bib22" id="ref68">22</reflink>]). Through a two-phase process involving exploratory and confirmatory factor analyses (Churchill, [<reflink idref="bib9" id="ref69">9</reflink>]; Hinkin, [<reflink idref="bib21" id="ref70">21</reflink>]), the resulting STEM Interest Scale (SIS) emerged as a multi-dimensional construct. The resultant STEM Interest Scale (SIS) consists of four distinct psychological factors: intrinsic motivation, self-efficacy, self-concept, and career aspirations. These factors collectively accounted for a significant portion of the total variance and demonstrated satisfactory reliability and validity.</p> <p>Aligned with theoretical frameworks such as self-determination theory and social cognitive career theory, the SIS captures the various dimensions that influence students' interest and engagement in STEM disciplines (Bandura, [<reflink idref="bib7" id="ref71">7</reflink>]; Hidi & Renninger, [<reflink idref="bib19" id="ref72">19</reflink>]; Lent et al., [<reflink idref="bib25" id="ref73">25</reflink>]). Consequently, it offers a nuanced and meaningful assessment of learners' interest level in STEM discipline, providing valuable insights for both researchers and practitioners. For researchers, the SIS serves as a valuable tool to investigate the antecedents, consequences, and correlates of STEM interest, aiding in the identification of intervention opportunities to bolster STEM engagement among students.</p> <p>The proposed scale has both theoretical and practical implications as it provides valuable insights into students' motivations, self-concept, efficacy, and aspirations within STEM fields. This facilitates policymakers, educators, and counselors in designing and delivering effective curricula, STEM education programs, and interventions. However, its effectiveness can only be determined through a longitudinal study. The SIS facilitates a deeper understanding of students' interest in STEM fields by elucidating the nomological network between STEM interest and intent to drop out. Ultimately, it supports educational institutions to improve participation and success rates in STEM education.</p> <hd id="AN0186780440-19">Conclusion</hd> <p>The development and validation of the STEM Interest scale (SIS) have elucidated that it is a multifaceted psychological construct. Its multidimensional nature provides valuable insights beyond traditional outcome-oriented perspectives, such as career interests. By exploring dimensions such as intrinsic motivation, self-efficacy, self-concept, and employment aspiration, this scale offers a nuanced understanding of STEM interest, aligning with contemporary theories and frameworks. Its validity and reliability have been confirmed through rigorous psychometric analyses, including both exploratory and confirmatory factor analyses, distinguishing it from other instruments in the field.</p> <p>Furthermore, the study's sample predominantly consists of expatriates, which enhances the research by incorporating a wide range of nationalities. This heterogeneity extends the scale's generalizability, allowing for its application across various geographic and cultural contexts with minimal modifications. The STEM Interest scale plays a key role in encouraging wider participation and sustained commitment in STEM fields, which is essential for developing a skilled and diverse workforce in these critical sectors.</p> <hd id="AN0186780440-20">Authors' Contributions</hd> <p>ZA: conceptualization; methodology; validation; writing—review and editing; project administration; funding acquisition. AS: methodology; formal analysis; writing—original draft. NS: data curation; MA: data curation. NJA: writing—review and editing; funding acquisition. All authors read and approved the final manuscript.</p> <hd id="AN0186780440-21">Funding</hd> <p>Open Access funding provided by the Qatar National Library. The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. The work was funded by Qatar University (Grant QUCG-YSC-22/23–485).</p> <hd id="AN0186780440-22">Data Availability</hd> <p>The raw data supporting the conclusion of this article will be made available by the authors without undue reservation.</p> <hd id="AN0186780440-23">Declarations</hd> <p></p> <hd id="AN0186780440-24">Ethics Approval and Consent to Participate</hd> <p>The study conducted was approved by the Institutional Review Board of Qatar University (QU-IRB 1721-EA/22). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.</p> <hd id="AN0186780440-25">Competing Interests</hd> <p>The authors declare that they have no competing interests.</p> <hd id="AN0186780440-26">Supplementary Information</hd> <p>Below is the link to the electronic supplementary material.</p> <p>Graph: Supplementary file1 (DOCX 24 KB)</p> <hd id="AN0186780440-27">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0186780440-28"> <title> References </title> <blist> <bibl id="bib1" idref="ref3" type="bt">1</bibl> <bibtext> Ahmad, Z, Ammar, M, Siby, N, Bhadra, J, Sellami, A, & Al-Thani, N. J. (2023). Do research experience programs promote capacity building in Qatar: investigating the trend and participation differences. Heliyon, 9(11).</bibtext> </blist> <blist> <bibl id="bib2" idref="ref33" type="bt">2</bibl> <bibtext> Ahmed W, Mudrey RR. The role of motivational factors in predicting STEM career aspirations. International Journal of School & Educational Psychology. 2019; 7; 3: 201-214</bibtext> </blist> <blist> <bibl id="bib3" idref="ref13" type="bt">3</bibl> <bibtext> Allen J, Robbins S. Effects of interest–major congruence, motivation, and academic performance on timely degree attainment. Journal of Counseling Psychology. 2010; 57; 1: 23</bibtext> </blist> <blist> <bibl id="bib4" idref="ref57" type="bt">4</bibl> <bibtext> Aulakh PS, Gencturk EF. International principal–agent relationships: Control, governance and performance. Industrial Marketing Management. 2000; 29; 6: 521-538</bibtext> </blist> <blist> <bibl id="bib5" idref="ref19" type="bt">5</bibl> <bibtext> Bandura A. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review. 1977; 84; 2: 191</bibtext> </blist> <blist> <bibl id="bib6" idref="ref10" type="bt">6</bibl> <bibtext> Bandura A. Self-efficacy: The exercise of control. 1997; Freeman</bibtext> </blist> <blist> <bibl id="bib7" idref="ref20" type="bt">7</bibl> <bibtext> Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23–28).</bibtext> </blist> <blist> <bibl id="bib8" idref="ref62" type="bt">8</bibl> <bibtext> Chachashvili-Bolotin S, Milner-Bolotin M, Lissitsa S. Examination of factors predicting secondary students' interest in tertiary STEM education. International Journal of Science Education. 2016; 38; 3: 366-390</bibtext> </blist> <blist> <bibl id="bib9" idref="ref37" type="bt">9</bibl> <bibtext> Churchill GA Jr. A paradigm for developing better measures of marketing constructs. Journal of Marketing Research. 1979; 16; 1: 64-73</bibtext> </blist> <blist> <bibtext> Cronbach LJ. Coefficient alpha and the internal structure of tests. psychometrika. 1951; 16; 3: 297-334</bibtext> </blist> <blist> <bibtext> Dagley M, Georgiopoulos M, Reece A, Young C. Increasing retention and graduation rates through a STEM learning community. Journal of College Student Retention: Research, Theory & Practice. 2016; 18; 2: 167-182</bibtext> </blist> <blist> <bibtext> Deci EL, Ryan RM. The general causality orientations scale: Self-determination in personality. Journal of Research in Personality. 1985; 19; 2: 109-134</bibtext> </blist> <blist> <bibtext> Dierks PO, Höffler TN, Blankenburg JS, Peters H, Parchmann I. Interest in science: A RIASEC-based analysis of students' interests. International Journal of Science Education. 2016; 38; 2: 238-258</bibtext> </blist> <blist> <bibtext> Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 1981; 18; 1: 39-50</bibtext> </blist> <blist> <bibtext> Franks AD, Capraro MM. Motivated for STEM: Developing an understanding of highly motivated students' self-concept in STEM education. Science Educator. 2019; 27; 1: 60-69</bibtext> </blist> <blist> <bibtext> Hair, J. F, Black, W. C, Babin, B. J, & Anderson, R. E. (2010). Multivariate data analysis, Prentice Hall, New Jersey. Technometrics, 15(3).</bibtext> </blist> <blist> <bibtext> Hazari Z, Potvin G, Cribbs JD, Godwin A, Scott TD, Klotz L. Interest in STEM is contagious for students in biology, chemistry, and physics classes. Science Advances. 2017; 3; 8e1700046</bibtext> </blist> <blist> <bibtext> Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science. 2015; 43: 115-135</bibtext> </blist> <blist> <bibtext> Hidi S, Renninger KA. The four-phase model of interest development. Educational Psychologist. 2006; 41; 2: 111-127</bibtext> </blist> <blist> <bibtext> Hillman SJ, Zeeman SI, Tilburg CE, List HE. My attitudes toward science (MATS): The development of a multidimensional instrument measuring students' science attitudes. Learning Environments Research. 2016; 19: 203-219</bibtext> </blist> <blist> <bibtext> Hinkin TR. A review of scale development practices in the study of organizations. Journal of Management. 1995; 21; 5: 967-988</bibtext> </blist> <blist> <bibtext> Hinkin TR. Scale development principles and practices. Research in Organizations: Foundations and Methods of Inquiry. 2005; 1: 161-179</bibtext> </blist> <blist> <bibtext> Honicke T, Broadbent J, Fuller-Tyszkiewicz M. Learner self-efficacy, goal orientation, and academic achievement: Exploring mediating and moderating relationships. Higher Education Research & Development. 2020; 39; 4: 689-703</bibtext> </blist> <blist> <bibtext> Kier MW, Blanchard MR, Osborne JW, Albert JL. The development of the STEM career interest survey (STEM-CIS). Research in Science Education. 2014; 44: 461-481</bibtext> </blist> <blist> <bibtext> Lent RW, Brown SD, Hackett G. Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior. 1994; 45; 1: 79-122</bibtext> </blist> <blist> <bibtext> Lin JSC, Hsieh PL. Assessing the self-service technology encounters: Development and validation of SSTQUAL scale. Journal of Retailing. 2011; 87; 2: 194-206</bibtext> </blist> <blist> <bibtext> Luo T, So WWM. Elementary students' perceptions of STEM professionals. International Journal of Technology and Design Education. 2023; 33; 4: 1369-1388</bibtext> </blist> <blist> <bibtext> Luo T, So WWM, Wan ZH, Li WC. STEM stereotypes predict students' STEM career interest via self-efficacy and outcome expectations. International Journal of STEM Education. 2021; 8: 1-13</bibtext> </blist> <blist> <bibtext> Lytle A, Shin JE. Incremental beliefs, STEM efficacy and STEM interest among first-year undergraduate students. Journal of Science Education and Technology. 2020; 29; 2: 272-281</bibtext> </blist> <blist> <bibtext> Maltese AV, Tai RH. Eyeballs in the fridge: Sources of early interest in science. International Journal of Science Education. 2010; 32; 5: 669-685</bibtext> </blist> <blist> <bibtext> Maltese AV, Tai RH. Pipeline persistence: Examining the association of educational experiences with earned degrees in STEM among US students. Science Education. 2011; 95; 5: 877-907</bibtext> </blist> <blist> <bibtext> Maltese AV, Melki CS, Wiebke HL. The nature of experiences responsible for the generation and maintenance of interest in STEM. Science Education. 2014; 98; 6: 937-962</bibtext> </blist> <blist> <bibtext> Mohd Shahali EH, Halim L, Rasul MS, Osman K, Mohamad Arsad N. Students' interest towards STEM: A longitudinal study. Research in Science & Technological Education. 2019; 37; 1: 71-89</bibtext> </blist> <blist> <bibtext> Murphy S, MacDonald A, Danaia L, Wang C. An analysis of Australian STEM education strategies. Policy Futures in Education. 2019; 17; 2: 122-139</bibtext> </blist> <blist> <bibtext> Nemoto, T, & Beglar, D. (2014). Likert-scale questionnaires. In JALT 2013 conference proceedings (pp. 1–8).</bibtext> </blist> <blist> <bibtext> Oh YJ, Jia Y, Lorentson M, LaBanca F. Development of the educational and career interest scale in science, technology, and mathematics for high school students. Journal of Science Education and Technology. 2013; 22: 780-790</bibtext> </blist> <blist> <bibtext> Peng TK, Kao YT, Lin CC. Common method variation in management study: Question essence, influence, test and remedy. Journal of Management. 2006; 23; 1: 77-98</bibtext> </blist> <blist> <bibtext> Rogers CR. The necessary and sufficient conditions of therapeutic personality change. Journal of Consulting Psychology. 1957; 21; 2: 95</bibtext> </blist> <blist> <bibtext> Schumacker, E, & Lomax, G. (2016). A beginner's guide to structural equation modeling. 4th edtn.</bibtext> </blist> <blist> <bibtext> Schunk, D. H, & DiBenedetto, M. K. (2021). Self-efficacy and human motivation. In Advances in motivation science (Vol. 8, pp. 153–179). Elsevier.</bibtext> </blist> <blist> <bibtext> Schwarz, J. (2011). Research methodology: tools. Applied data analysis (with SPSS). Lecture, 2.</bibtext> </blist> <blist> <bibtext> Sellami AL, Al-Ali A, Allouh A, Alhazbi S. Student attitudes and interests in STEM in Qatar through the lens of the social cognitive theory. Sustainability. 2023; 15; 9: 7504</bibtext> </blist> <blist> <bibtext> Staus NL, Lesseig K, Lamb R, Falk J, Dierking L. Validation of a measure of STEM interest for adolescents. International Journal of Science and Mathematics Education. 2020; 18: 279-293</bibtext> </blist> <blist> <bibtext> Tyler-Wood T, Knezek G, Christensen R. Instruments for assessing interest in STEM content and careers. Journal of Technology and Teacher Education. 2010; 18; 2: 345-368</bibtext> </blist> <blist> <bibtext> Unfried A, Faber M, Stanhope DS, Wiebe E. The development and validation of a measure of student attitudes toward science, technology, engineering, and math (S-STEM). Journal of Psychoeducational Assessment. 2015; 33; 7: 622-639</bibtext> </blist> <blist> <bibtext> van den Hurk A, Meelissen M, van Langen A. Interventions in education to prevent STEM pipeline leakage. International Journal of Science Education. 2019; 41; 2: 150-164</bibtext> </blist> <blist> <bibtext> Veneziano L, Hooper J. A method for quantifying content validity of health-related questionnaires. American Journal of Health Behavior. 1997; 21; 1: 67-70</bibtext> </blist> <blist> <bibtext> Vulperhorst JP, Wessels KR, Bakker A, Akkerman SF. How do STEM-interested students pursue multiple interests in their higher educational choice?. International Journal of Science Education. 2018; 40; 8: 828-846</bibtext> </blist> <blist> <bibtext> Wang MT, Degol J. Motivational pathways to STEM career choices: Using expectancy–value perspective to understand individual and gender differences in STEM fields. Developmental Review. 2013; 33; 4: 304-340</bibtext> </blist> <blist> <bibtext> Wang MT, Ye F, Degol JL. Who chooses STEM careers? Using a relative cognitive strength and interest model to predict careers in science, technology, engineering, and mathematics. Journal of youth and adolescence. 2017; 46: 1805-1820</bibtext> </blist> <blist> <bibtext> Xu YJ, Webber KL. College student retention on a racially diverse campus: A theoretically guided reality check. Journal of College Student Retention: Research, Theory & Practice. 2018; 20; 1: 2-28</bibtext> </blist> <blist> <bibtext> Zaharin NL, Sharif S, Bikar Singh SS, Talin R, Mariappan M, Mohanaraj N, Suppiah P. Promoting students' interest, attitude and intrinsic motivation towards learning STEM through minimalist robot education programme. International Journal of Service Management and Sustainability (IJSMS). 2019; 4; 1: 1-26</bibtext> </blist> <blist> <bibtext> Zaichkowsky JL. Measuring the involvement construct. Journal of Consumer Research. 1985; 12; 3: 341-352</bibtext> </blist> </ref> <aug> <p>By Zubair Ahmad; Almaas Sultana; Nitha Siby; Mohammad Ammar and Noora J. Al-Thani</p> <p>Reported by Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib42" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib48" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib11" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib29" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib32" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib43" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib44" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib45" firstref="ref9"></nolink> <nolink nlid="nl9" bibid="bib13" firstref="ref11"></nolink> <nolink nlid="nl10" bibid="bib17" firstref="ref12"></nolink> <nolink nlid="nl11" bibid="bib19" firstref="ref14"></nolink> <nolink nlid="nl12" bibid="bib33" firstref="ref15"></nolink> <nolink nlid="nl13" bibid="bib34" firstref="ref17"></nolink> <nolink nlid="nl14" bibid="bib12" firstref="ref18"></nolink> <nolink nlid="nl15" bibid="bib38" firstref="ref21"></nolink> <nolink nlid="nl16" bibid="bib25" firstref="ref22"></nolink> <nolink nlid="nl17" bibid="bib52" firstref="ref25"></nolink> <nolink nlid="nl18" bibid="bib31" firstref="ref26"></nolink> <nolink nlid="nl19" bibid="bib49" firstref="ref27"></nolink> <nolink nlid="nl20" bibid="bib40" firstref="ref29"></nolink> <nolink nlid="nl21" bibid="bib15" firstref="ref30"></nolink> <nolink nlid="nl22" bibid="bib23" firstref="ref31"></nolink> <nolink nlid="nl23" bibid="bib28" firstref="ref34"></nolink> <nolink nlid="nl24" bibid="bib30" firstref="ref35"></nolink> <nolink nlid="nl25" bibid="bib50" firstref="ref36"></nolink> <nolink nlid="nl26" bibid="bib21" firstref="ref38"></nolink> <nolink nlid="nl27" bibid="bib53" firstref="ref39"></nolink> <nolink nlid="nl28" bibid="bib26" firstref="ref43"></nolink> <nolink nlid="nl29" bibid="bib41" firstref="ref46"></nolink> <nolink nlid="nl30" bibid="bib35" firstref="ref48"></nolink> <nolink nlid="nl31" bibid="bib47" firstref="ref49"></nolink> <nolink nlid="nl32" bibid="bib16" firstref="ref51"></nolink> <nolink nlid="nl33" bibid="bib14" firstref="ref52"></nolink> <nolink nlid="nl34" bibid="bib39" firstref="ref53"></nolink> <nolink nlid="nl35" bibid="bib10" firstref="ref54"></nolink> <nolink nlid="nl36" bibid="bib37" firstref="ref58"></nolink> <nolink nlid="nl37" bibid="bib51" firstref="ref59"></nolink> <nolink nlid="nl38" bibid="bib27" firstref="ref60"></nolink> <nolink nlid="nl39" bibid="bib46" firstref="ref63"></nolink> <nolink nlid="nl40" bibid="bib18" firstref="ref65"></nolink> <nolink nlid="nl41" bibid="bib22" firstref="ref68"></nolink>
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  Label: Title
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  Data: A Multi-Dimensional Scale for Measuring Undergraduates Interest in STEM Disciplines
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  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Zubair+Ahmad%22">Zubair Ahmad</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-6606-2269">0000-0002-6606-2269</externalLink>)<br /><searchLink fieldCode="AR" term="%22Almaas+Sultana%22">Almaas Sultana</searchLink><br /><searchLink fieldCode="AR" term="%22Nitha+Siby%22">Nitha Siby</searchLink><br /><searchLink fieldCode="AR" term="%22Mohammad+Ammar%22">Mohammad Ammar</searchLink><br /><searchLink fieldCode="AR" term="%22Noora+J%2E+Al-Thani%22">Noora J. Al-Thani</searchLink>
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  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Science+Education+and+Technology%22"><i>Journal of Science Education and Technology</i></searchLink>. 2025 34(4):611-620.
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  Label: Availability
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 10
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– 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="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Interests%22">Student Interests</searchLink><br /><searchLink fieldCode="DE" term="%22Interest+Inventories%22">Interest Inventories</searchLink><br /><searchLink fieldCode="DE" term="%22STEM+Education%22">STEM Education</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Validity%22">Test Validity</searchLink><br /><searchLink fieldCode="DE" term="%22Motivation%22">Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Concept%22">Self Concept</searchLink><br /><searchLink fieldCode="DE" term="%22Occupational+Aspiration%22">Occupational Aspiration</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Reliability%22">Test Reliability</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10956-024-10140-w
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1059-0145<br />1573-1839
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: One of the major challenges faced by the education system today is the lack of interest exhibited by undergraduates in Science, Technology, Engineering, and Mathematics (STEM) disciplines. This is particularly concerning as the world is becoming increasingly technology-driven, and a skilled workforce is necessary to meet future demands. Therefore, fostering interest among undergraduates in STEM fields is imperative to improve their engagement and persistence in these disciplines. Numerous initiatives have been undertaken to enhance students' STEM interests in formal, non-formal, and informal learning settings. However, assessing the effectiveness of these initiatives requires a robust and validated measurement tool grounded in theoretical and empirical evidence. Without a valid and reliable instrument, it would be challenging to determine the effectiveness of these initiatives in promoting STEM education and interest among undergraduates. This study presents a STEM Interest Scale (SIS) that captures diverse psychological factors that affect students' interest in STEM. To develop this scale, the study employs a cross-sectional quantitative design. The data collection process involved two phases for developing and validating the scale. In phase I, 280 participants were surveyed to perform exploratory factor analysis (EFA) to identify the underlying dimensions of STEM interest. In phase II, a sample of 266 students was used to assess the psychometric characteristics of the 'STEM Interest Scale (SIS) using confirmatory factor analysis (CFA) and nomological validity. The outcome of the EFA revealed that the STEM Interest scale is comprised of four psychological factors: intrinsic motivation, self-efficacy, self-concept, and employment aspiration, while the CFA and nomological network confirm the validity of these factors. The present research is a pioneering effort to holistically capture STEM interest, thereby paving the way for informed interventions in STEM education.
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  Data: As Provided
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  Label: Entry Date
  Group: Date
  Data: 2025
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  Label: Accession Number
  Group: ID
  Data: EJ1477799
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1477799
RecordInfo BibRecord:
  BibEntity:
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      – Type: doi
        Value: 10.1007/s10956-024-10140-w
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 611
    Subjects:
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Student Interests
        Type: general
      – SubjectFull: Interest Inventories
        Type: general
      – SubjectFull: STEM Education
        Type: general
      – SubjectFull: Test Validity
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      – SubjectFull: Motivation
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      – SubjectFull: Self Efficacy
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      – SubjectFull: Self Concept
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      – SubjectFull: Occupational Aspiration
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      – SubjectFull: Test Reliability
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      – TitleFull: A Multi-Dimensional Scale for Measuring Undergraduates Interest in STEM Disciplines
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