Home Education Revealing the Power of Minds Online: Validating Instruments for Reflective Thinking, Self-Efficacy, and Self-Regulated Learning
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Revealing the Power of Minds Online: Validating Instruments for Reflective Thinking, Self-Efficacy, and Self-Regulated Learning

  • Amalia Sapriati EMAIL logo , Mestika Sekarwinahyu , Maya Puspitasari and Fitria Amastini
Published/Copyright: May 7, 2025
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Open Education Studies
From the journal Open Education Studies Volume 7 Issue 1

Abstract

This study presents a new instrument for assessing reflective thinking, self-efficacy, and self-regulated learning (SRL) among Universitas Terbuka postgraduate students registered in an online Research Methods course. The study validates the instrument’s dependability (Cronbach’s alpha = 0.918) and builds a strong factor structure by means of statistical techniques including factor analysis and partial least squares structural equation modeling, therefore addressing 56% of the variance. Strong interrelationships between reflective thinking, self-efficacy, and SRL are revealed by the study, therefore underscoring their joint functions in improving online learning environments. Although the results highlight the need for these abilities in promoting academic performance in higher education, the study warns against generalizing results considering the particular demographic of the participants. It demands more study conducted in several learning environments. This article might provide useful insights for teachers and researchers looking to develop these important crucial abilities in online learning environments. It may then lead to enhance student results and results in more efficient decision-making in remote education contexts.

Keywords: educational assessment; higher education; online learning environments; open and distance education

1 Introductıon

In succeeding at higher education institutions, having reflective thinking skills, self-efficacy, and self-regulated learning (SRL) abilities are fundamental (Brundiers, et al., 2021; Chen, Hwang, & Chang, 2019; De Silva, 2020; Erdogan, 2019; Fust, Jenert, & Winkler, 2018; Higgins, Frankland, & Rathner, 2021; Peel, 2019). To succeed in this environment, they must cultivate key competencies that have been widely recognized on a global scale. Among these crucial abilities are reflective thinking skills, which allow students to analyse their learning experiences and improve their decision-making; self-efficacy, which fosters confidence in their ability to achieve academic goals; and SRL, which enables them to take control of their own learning process, set goals, and manage their progress effectively.

Having reflective thinking skills helps individuals to study their personal experiences, beliefs, and actions to develop deeper insights and make better decisions (Akpur, 2020; Choy, Lee, & Sedhu, 2019; Choy, Dinham, Yim, & Williams, 2021; Greenberger, 2020; Hong & Choi, 2011; Orakcı, 2021; Schunk & Zimmerman, 1998). Reflective thinking skills may help students identify their strengths and weaknesses, identify areas where they can improve, and develop strategies for continuous growth. Likewise, SRL enables students to take control of their education by setting goals, planning their study strategies, and monitoring their own progress (Al-Abyadh & Abdel Azeem, 2022; Ateş Akdeniz, 2023; Bernacki et al., 2023; Dörrenbächer-Ulrich, Weißenfels, Russer, & Perels, et al., 2021; Martinez-Lopez, Yot, Tuovila, & Perera-Rodríguez, et al., 2017; Welsh & Dehler, 2013; Yavuzalp, & Bahçivan, 2020; Yan, 2020; Zeidner & Stoeger, 2019). A sense of ownership and agency in the educational process has been managed to empower students to become active, engaged, and resourceful lifelong learners.

Dewey (1933) and Moon (1999) defined reflective thinking as a metacognitive process involving the critical review of one’s ideas, beliefs, and behaviour. Moon (1999) calls it a rigorous, orderly approach to self-reflection that lets people reach deep insights, challenge presumptions, and make wise decisions. Reflective thinking has been connected to a range of positive outcomes, including improved problem-solving skills, enhanced cognitive engagement, and higher academic achievement across many disciplines (Aydoğmuş & Şentürk, 2023; Hatton & Smith, 1995; Karaoglan-yılmaz, Ustun, Zhang, & Yılmaz, 2023; Umar, 2023; Yan, Sun, Zhou, Yang, & Tian, 2023). This method can help one succeed academically and also negotiate difficult problems with more clarity and confidence.

Self-efficacy is “the ability ‘to achieve specified levels of performance that exert influence over events impacting their life’” (Bandura, 1994). Particularly in educational environments, self-efficacy relates to a person’s belief in their capacity to face obstacles and reach particular goals (Al-Abyadh & Abdel Azeem, 2022; Bandura, 1993, 2006; Schunk, 1995). This self-confidence profoundly affects students’ perceptions of their capacity to perform academic tasks, adeptly employ technology for learning, and autonomously oversee their educational endeavours. Studies on self-efficacy in open higher education have underscored the significance of cultivating self-efficacy within this framework (Duchatelet & Donche, 2019).

In addition to impacting academic performance, self-efficacy profoundly influences students’ emotional well-being, which is essential for maintaining engagement in school and fostering a nurturing learning environment. (Dai, 2024; Heng & Chu, 2023; Hussain, Mkpojiogu, & Ezekwudo, 2021; Muñoz, 2021; Orakcı, Yüreğilli Göksu, & Karagöz, 2023; Tang, Tseng, & Tang, 2022; Teng, Wang, & Wu, 2023). Moreover, self-efficacy is necessary for the development of self-regulated learners who efficiently define educational goals, apply successful tactics, assess their development, and participate in introspection of their learning events. By emphasizing the improvement of self-efficacy, teachers enable students to approach educational obstacles with confidence, therefore assuring they are appropriately prepared for success in many educational environments and lifetime learning.

SRL is the ability of students to actively monitor and direct their educational processes including goal development, method application, self-assessment, and self-reflection (Schunk & Zimmerman, 2013; Zimmerman & Schunk, 2011). Learners actively engage in their educational experiences to improve their learning outcomes, so encompassing the cognitive, behavioural, motivating, and emotional aspects of learning (Albelbisi, Al-Adwan, & Habibi, 2021; Edisherashvili, Saks, Pedaste, & Leijen, 2022; Higgins et al., 2021; van der Graaf et al., 2022). Within the framework of SRL, learners are regarded as proactive agents in their educational journey. They establish individual academic objectives, implement strategies to attain these objectives, assess their progress, and evaluate their learning results to make requisite modifications. Three cyclical phases define the SRL framework: foresight (planning and goal development), performance (strategy implementation and monitoring), and self-reflection (evaluation and adaptation). Having SRL skills is important in the modern classroom to experience the demands of a knowledge-based culture. Self-regulating skill in this context means letting students take accountability for their educational path (Bernacki, et al., 2023; Sadeck, Moyo, Tunjera, & Chigona, 2023; Su, Noordin, & Yang, 2023; Zeidner & Stoeger, 2019). This self-autonomy might enhance academic achievement and develop essential skills, including critical thinking, problem-solving, and self-regulation (Al-Adwan, et al., 2024; Alshammari & Alkhwaldi, 2025; Chang, Panjaburee, Lin, Lai, & Hwang, 2022; Liu, Hou, Tu, Wang, & Hwang, 2023; Niu, Cheng, Duan, & Zhang, 2022; Wu, 2023). SRL can thus strengthen a sense of agency and empowerment in students, transforming the students into active participants in their educational advancement rather than passive recipients of knowledge (Peel, 2019; Singh & Allers, 2022; Zacarian & Silverstone, 2020). Institutions can prepare the students for both academic achievement and continuous personal and professional development in a dynamic global environment by creating SRL environment (Abdulhay, 2015; Ateş Akdeniz, 2023; Cleary, Callan, & Pawlo, 2020; Peel, 2019; Sadeck et al., 2023; Su et al., 2023).

At Universitas Terbuka, a higher education institution that offers open and distance learning, it is necessary to foster reflective thinking, self-efficacy, and SRL. Chen et al (2019) and Tsingos, Bosnic-Anticevich, and Smith (2015) argue that reflective thinking plays an important role in improving students’ deep learning and enhancing their metacognitive awareness. This form of critical thinking helps students to evaluate their learning experiences critically, connect to new knowledge with previous ones, and develop a more nuanced understanding of difficult ideas (Acquah & Commins, 2015; Christian, McCarty, & Brown, 2021; Howell, 2021; McGarr, 2021; Veine et al., 2020; Welsh & Dehler, 2013).

Online learning’s asynchronous character as well as the variety of backgrounds and demands of the students emphasize the need for a proactive and flexible approach to education. Postgraduate students, in particular, have to show a great degree of autonomy and self-control since they participate in advanced studies and research. Designing efficient educational interventions and support systems thus depends on knowing how postgraduate students engage in reflective and SRL in online contexts. The dearth of validated instruments, especially meant to evaluate reflective thinking, self-efficacy, and SRL in online learning environments, marks a major gap in the literature. This emphasizes how urgently technologies capturing the subtleties of reflective thinking and SRL in digital education contexts must be developed and validated. The research questions addressed are as follows:

  1. How effectively do the items within the educational scale represent the constructs of Reflective Thinking, Self-Efficacy, and SRL?

  2. How reliable are the measurements used to assess these constructs in the context of educational research?

  3. How do the constructs of Reflective Thinking, Self-Efficacy, SRL, Discussion, Task, and Exam Performance interrelate?

  4. Considering the unique case of single-item constructs like Discussion, Task, and Exam, what are the implications for scale development in educational research?

  5. How do demographic and academic background factors (such as age, field of study, and academic level) affect the measurements of reflective thinking, self-efficacy, and SRL using the developed instrument?

By addressing these questions, this study contributes to the advancement of assessment practices in online and distance education, providing a stronger empirical foundation for understanding student learning behaviours in digital environments.

2 Method

2.1 Participants

The study involved 91 out of 131 postgraduate students enrolled in the course of Research Methods in Education at Universitas Terbuka; a higher education institution which supports open and distance education in Indonesia. These students were selected purposively because their coursework required assignments incorporating three key elements: self-reflective thinking, self-efficacy, and SRL. The sample size of 91 participants (approximately 70% of the total enrolled students) was deemed adequate, providing a sufficient number of responses to ensure statistical reliability while maintaining a manageable scope for data analysis.

2.2 Data Collection and Analysis

Participants were sent reflective thinking, self-efficacy, and SRL designed questionnaires using the university’s online learning portal. The researchers in this study provided clear direction that honesty and care in their answers are the participants’ priority, thus ensuring data accuracy and dependability. The study also included inferential and descriptive statistics to present a comprehensive understanding of the data. Factor analysis revealed the underlying structure of the assessed components, thereby exposing various aspects of reflective thinking ability and self-directed learning capacity. This approach allowed for a sophisticated analysis of the structures, enhancing the depth of inquiry.

Further investigation included examining the complex interactions between constructs and the validity and dependability of assessment tools using partial least squares structural equation modelling (PLS-SEM). The PLS-SEM analysis incorporated rigorous tests for validity (construct validity) and reliability (Cronbach’s alpha) to ensure the robustness of the measurement model. Without assuming normal data distribution, this systematic decision was intentional, based on its appropriateness for exploratory research and complex models. Aiming to test reflective thinking skills and SRL capacities among postgraduate students in online learning contexts, the strict usage of these analytical methodologies intended to evaluate the validity and reliability of the designed questionnaires. Including PLS-SEM, the researchers’ methodological approach was meant to provide insightful analysis of evaluation techniques in distance education modes and help untangle the complex links among these constructs. This study emphasizes the important role researchers play in guaranteeing the integrity and rigor of data collection and processing techniques in educational research.

3 Findings

3.1 Validity of Construct Items in Reflective Thinking Skills, Self-Efficacy, and SRL

Table 1 presents the results of a factor analysis designed to validate the construct validity of a questionnaire measuring several constructs related to learning and reflective thinking. Each row represents a questionnaire item, while each column represents a construct. The factor loading values indicate how strongly each item is associated with its respective construct.

Table 1

Validity test of loading factor

Variables Indicators Items Loading factor
Self-efficacy Generality G3 I am confident of succeeding at tasks that cover a wide range of areas 0.878
Magnitude M3 I am confident that I will successfully complete tasks that require a complex and sophisticated level of thinking 0.922
Strength S1 I remain confident that I can achieve my target despite many obstacles 0.799
Self-regulated learning Metacognitive activities during learning MDL2 I have a specific goal for each strategy I use in this online tutorial 0.840
MDL3 I know what strategies I used when I studied for this online tutorial 0.789
MDL4 I changed my strategy when I wasn’t making any progress while studying this online tutorial 0.872
MDL5 I perform periodic reviews to help me understand important relationships in these online tutorials 0.741
Metacognitive activities after learning MAL2 I ask myself how well I achieved my goal after I finished doing this tutorial online 0.716
MAL3 After studying for this online tutorial I reflect on what I have learned 0.791
MAL4 I found myself analysing the usefulness of strategies after I studied for this online tutorial 0.817
MAL5 I ask myself if there is another way to do something after I finish studying for this online tutorial 0.770
MAL6 After studying this online tutorial, I thought about the study strategy I used 0.816
Time management TM5 I allocated study time for this online tutorial 0.716
Reflective thinking Lifelong learning BSH02 I try to correct mistakes and learn Educational Research Methods from experience to be more successful 0.764
BSH06 I consider the performance I already have to integrate how to learn Educational Research Methods with things that are relevant now and in the future 0.717
Self-evaluation MED02 I pay attention to self-discovery in studying Educational Research Methods thus I can apply knowledge to make myself better 0.760
MED06 I consider feedback in studying Educational Research Methods as something that can improve the quality of my work so that my future performance will be better 0.796
MED07 I think that feedback in studying Educational Research Methods helps me understand things around me better 0.835
MED10 I think about what to do in studying Educational Research Methods related disciplines to improve my performance 0.753
MED11 I understand that studying Educational Research Methods can bring out things I like and together with feedback will improve the quality of my performance 0.811
Discussion 1.000
Task 1.000
Exam 1.000

3.2 The Scale Identification of Constructs and Their Items

This section concentrates on identifying the different constructs evaluated within the educational setting and the individual objects that embody these structures. For instance, structures such as Reflective Thinking, Self-Efficacy, SRL, Discussion, Task, and Exam are recognized. Each construct is linked to a collection of items, and their loadings are assessed to determine their efficacy in assessing the designated constructs. This section presents a comprehensive review of the constructions being analysed and the preliminary collection of items employed to operationalize them.

The loading factors for variables associated with reflective thinking (BSH02, BSH06, MED2, MED6, MED7, MED10, and MED11) vary from 0.717 to 0.835, showing a robust and favourable connection with the construct. This implies that these tools reasonably assess the responders’ reflective thinking ability. Reflective thinking is self-assessment, processing of comments, and contemplation of learning events; it is both a personal and intellectual development’s tool.

Self-efficacy (G3, M3, and S1) items exhibit rather strong loading factors ranging from 0.799 to 0.922. This indicates a strong assessment of students’ confidence in their ability to sustain endurance against adversity and participate in demanding and challenging activities with complexity. The great relationship between these elements with self-efficacy highlights the significance of motivating a strong belief in one’s capacities in educational situations. Improving self-efficacy can result in superior academic achievement, heightened motivation, and greater resilience in overcoming learning challenges.

Loading factors for items linked with SRL (MDL2–5, MAL2–6, and TM5) vary from 0.716 to 0.872. The findings indicated a significant connection with this construct. These tools highlighted their usefulness in measuring SRL capacity since they examined metacognitive processes before and after learning as well as with time management abilities. The results emphasized the necessity of SRL competencies in an effective online learning environment including metacognitive methods and temporal organization. It suggested that improving SRL skills could help students to plan, monitor, and assess better their learning process, leading them to have more successful and efficient educational experiences.

One item with a 1.000 loading factor signals the end of the debate. Like assignment and test frameworks, the optimal loading factor for lectures denotes an appropriate appraisal of students’ engagement in conversation. This highlights the efficacy of adopting debates as a teaching instrument in supplementing learning experiences. The findings suggested that participating in discussions can increase students’ comprehension, analytical reasoning, and cooperative learning. The independent items in this study: Task and Exam have a loading factor of 1.000. The optimal loading factor for these structures suggests that the questions precisely and indisputably measure the task and exam-related qualities. This suggests that these parts of the learning process are clearly outlined and accurately reflected by the questionnaire items. The direct assessment of task and exam constructs can thus offer unambiguous insight into students’ performance and opinions towards these specific educational elements.

3.3 Construct Validity and Reliability

The emphasis now turns to examining the complete construct validity of the measuring scale. Construct validity applies to the degree to which a scale properly measures the theoretical constructs it wants to evaluate. The analysis of component loadings is vital for determining construct validity; robust loadings signal a high level of construct validity, whereas weak or negative loadings imply probable issues. This section analyses the relationship between items and their theoretical constructions, highlighting the scale’s efficacy in encapsulating the dimensions and complexities of the structures in question. Moreover, particular observations within conceptions like Reflective Thinking, Self-Efficacy, and SRL underscore the efficacy of certain items in encapsulating the essence of these educational occurrences.

Items like BSH02, G, and MAL2 exhibit notable increases in loadings, indicating clearer representations of their respective constructs. Items such as BSH02, BSH06, MED02, MED06, MED07, and MED10 demonstrate increased loadings, implying a clearer representation of the reflective thinking construct. This suggests that these items are more suited to capture the core of careful consideration. As markers of SRL, the items MAL2, MAL3, MAL4, MAL5, MAL6, MDL2, MDL3, MDL4, MDL5, and TM5 show noteworthy and consistent loadings. These objects are regarded as consistent measures of this notion. With rather large loadings, G3, M3, and S1 show significant improvements in the clarity and accuracy of the self-efficacy notion. These tools should be rather helpful for determining respondents’ degrees of self-efficacy. With ideal loadings of 1.000, the constructions of discussion are clearly important for the measurement scale and might be either main or single-item indicators for them. This emphasizes their relevance in capturing, in the context of the study, the core of communication, task completion, and evaluation.

3.4 Reliability of Construct Items in Reflective Thinking, Self-Efficacy, and SRL

Table 2 showed that with a considerably lower AVE (0.605), Reflective Thinking also demonstrates outstanding dependability (Cronbach’s Alpha = 0.891, rho_A = 0.895, Composite Reliability = 0.99) hence showing good internal consistency among the items and sufficient convergent validity. Although item internal consistency is good, the somewhat lower AVE suggests that item variance might need some work in explanation. This implies alternative approaches to enhance the measuring model to raise its explanatory power even in cases when the items are internally consistent and might not entirely reflect the variance of the concept.

Table 2

Reliability test

Variables Cronbach’s alpha rho_A Composite reliability Average variance extracted (AVE)
Reflective thinking 0.891 0.895 0.914 0.605
Self-efficacy 0.835 0.842 0.901 0.753
Self-regulated learning 0.932 0.936 0.942 0.621
Discussion 1.000 1.000 1.000 1.000
Task 1.000 1.000 1.000 1.000
Exam 1.000 1.000 1.000 1.000

Strong dependability and validity indices for Self-Efficacy (Cronbach’s Alpha = 0.835, rho_A = 0.842, Composite Reliability = 0.901, AVE = 0.753) clearly illustrate the remarkable consistency and efficacy of the items used to measure this construct. These steps imply that the objects are valid indicators of the variance attributed to self-efficacy across several benchmarks. Strong values for Cronbach’s Alpha, rho_A, Composite Reliability, and AVE demonstrate the internal consistency and convergent validity of the questions, hence enhancing their dependability in evaluating respondent self-efficacy.

SRL demonstrates rather remarkable dependability (Cronbach’s Alpha = 0.932, rho_A = 0.9936, Composite Reliability = 0.942), therefore displaying outstanding internal consistency and good convergent validity with an AVE of 0.621. Although the AVE reveals the degree of convergence of the objects on the underlying construct, the high dependability values suggest that the objects are very consistent in evaluating the construct. These findings suggest that the objects capture the variance connected to SRL since they demonstrate outstanding internal consistency and convergent validity. Through reflective thinking, more studies could be necessary to precisely define the variance in the construct and modify the assessment technique.

Within this study, the perfect scores – 1.000 – achieved by the constructs of Discussion, Task, and Exam across all measures show remarkable validity and dependability. In practical research settings, such consistency in measurement outcomes is somewhat rare; hence, some uncertainty about the used method is justified. This could imply the use of a single item to assess each construct, therefore simplifying the measuring model but maybe oversimplifying the complexity of these constructs. On the other hand, it could reflect an overly simple attitude to measuring, therefore reducing the depth of information gained from these principles. Further research into the approach used to assess these constructions would provide an interesting examination of the validity and applicability of the measurement instrument.

4 Discussions and Conclusion

A complete investigation of concepts and their associated components within the educational context offers useful insights for measuring essential competencies and behaviours in online learning contexts. The findings highlighted the effectiveness of specific tools in encouraging students’ reflective thinking, self-efficacy, and SRL skills. Notably, reflective thinking items reveal a strong positive link with the idea, emphasizing the crucial function of self-assessment and reflection in supporting both personal and academic improvement (Banner, Rice, Schutte, Cosh, & Rock, 2024; Choy et al., 2019; Hong & Choi, 2011; Orakcı, 2021). Likewise, a strong connection between self-efficacy and learning outcomes highlights how building confidence and resilience in students can encourage their motivation and overall performance in the classroom (Al Ali & Saleh, 2022; Bandura, 2006; Boerchi, Magnano, & Lodi, 2021; Dixon, Hawe, & Hamilton, 2020; Mitchell et al., 2021; Schunk, 1995; Yavuzalp & Bahçivan, 2020). Furthermore, features connected to SRL stress the crucial significance of metacognitive methods and time management in obtaining effective online learning outcomes (De Silva, 2020; Dörrenbächer-Ulrich et al., 2021; Fan et al., 2022; Jansen, Van Leeuwen, Janssen, & Kester, 2018; Koivuniemi, Järvenoja, Järvelä, & Thomas, 2021).

Accurately assessing discourse, task performance, and test results through individual items shows how effective these tools are in capturing students’ engagement and perspectives on different learning activities. These findings have important implications for educational assessment and practice, providing educators and researchers with reliable tools to evaluate and strengthen key skills in online learning environments (Abuhassna et al., 2020; Akpur, 2020; Al-Abyadh & Abdel Azeem, 2022; De Backer, Van Keer, De Smedt, Merchie, & Valcke, 2022; Jiang, Chen, Lu, & Wang, 2021; Niu et al., 2022; Oguguo et al., 2021; Park & Kim, 2022; Qiu & Lee, 2020; Wei & Chou, 2020). Moving forward, further research is needed to validate these findings across different educational settings and refine assessment tools to ensure they remain accurate and relevant in measuring students’ online learning abilities. This study aimed to investigate and evaluate a scale intended to assess many educational constructs, emphasizing Reflective Thinking, Self-Efficacy, SRL, Discussion, Task, and Exam. Our validation process involved a thorough investigation of factor loadings to determine the links between items and their corresponding constructs. This study offers substantial remarks regarding the construct validity of the scale and its ramifications for subsequent scale development (Al Ali & Saleh, 2022; Banner et al., 2024; Choy et al., 2019; De Silva, 2020; Dixon et al., 2020; Fan et al., 2022; Hong & Choi, 2011; Jansen et al., 2018; Koivuniemi et al., 2021; Mitchell et al., 2021).

The constructs of Discussion, Task, and Exam, each represented by items with strong factor loadings, illustrate this approach. These findings suggest that certain methodological choices in scale development such as using single items to represent constructs or identifying them as key marker variables, can affect measurement results. Although these methodological choices may offer a simple assessment process, they also highlight the importance of meticulously choosing items that are both highly representative and theoretically substantiated.

Furthermore, the process of construct refinement evolved as a crucial phase in scale development. Constructs exhibiting consistently high loadings over numerous items signify clearly defined dimensions, while those with fewer items or varied loadings indicate regions requiring further enhancement. The refinement process entails a comprehensive theoretical and empirical review to guarantee that the scale precisely encapsulates the essence of the constructs (Banner, et al., 2024; Boerchi, et al., 2021; Choy, et al., 2019; Dixon, et al., 2020; Glassman, Kuznetcova, Peri, & Kim, 2021; Jansen, et al., 2018; Mitchell, et al., 2021; Sirota, Dewberry, Juanchich, Valuš, & Marshall, 2021).

The analysis presented in the reliability test and factor analysis tables offers a comprehensive look at the tools used to measure key educational and psychological concepts, such as Reflective Thinking, Self-Efficacy, SRL, as well as broader areas like Discussion, Task, and Exam performance. The reliability metrics – Cronbach’s Alpha, rho_A, Composite Reliability, and AVE – show that most of these constructs are highly consistent and reliable. In particular, Self-Efficacy, Reflective Thinking, and SRL stand out with especially strong reliability scores. This suggests that the questions or items tied to these constructs are effectively capturing the ideas they’re designed to measure (Banner et al., 2024; Boerchi et al., 2021; Choy et al., 2019; De Silva, 2020; Dixon et al., 2020; Fan et al., 2022; Glassman et al., 2021; Jansen et al., 2018; Mitchell et al., 2021; Sirota et al., 2021).

The appearance of negative loadings for some items in the factor analysis highlights the importance of taking a closer look at these specific items within the measurement model. Items that are reverse-coded or designed to capture opposing aspects of a construct can offer useful insights into how students think and perceive themselves. However, they can also create challenges when it comes to maintaining consistency and making sense of the results. Moving forward, it would be helpful to investigate whether these negative loadings point to issues like a mismatch in conceptual alignment, response biases, or the possibility that the constructs themselves are more complex than initially thought. Revising or rephrasing these items could enhance the clarity and reliability of the tool, making sure it accurately captures the nuances of reflective thinking, self-efficacy, and SRL. Additionally, talking directly to respondents through cognitive interviews might shed light on their confusion or misunderstandings when interpreting these items, helping to further refine the instrument.

4.1 Implications for Scale Development

The importance of key elements like Discussion, Task, and Exam within the measurement scale is highlighted by retaining their ideal loadings. This careful attention to constructing items and their loadings not only enhances the scale’s validity and reliability but also provides a deeper understanding of how educational constructs interact within the studied framework. Insights into construct identification, factor loadings, and construct validity guide the improvement and optimization of the measurement scale. This section explores ways to boost the scale’s validity and reliability through refining constructs and optimizing items. It underscores the necessity of iterative processes in scale development, where adjustments are made based on empirical evidence to ensure the scale accurately reflects the constructs it aims to measure (Choy et al., 2019; Dixon et al., 2020; Dörrenbächer-Ulrich et al., 2021; Jansen et al., 2018; Sabariego Puig, Sanchez-Marti, Ruiz-Bueno, & Sánchez-Santamaría, 2020; Varier, Kitsantas, Zhang, & Saroughi, 2021). Additionally, this part discusses the broader implications of the findings for educational research and practice, emphasizing the importance of thorough scale development in advancing our understanding of educational phenomena.

4.2 Impact of Demographics and Learning Environment Characteristics

The study indicated that the instrument seems competent to provide consistent assessments throughout a wide spectrum of students and online learning contexts. The conversation also emphasizes the need for more investigation to investigate how particular demographic elements and learning strategies affect the constructions assessed (Albus & Seufert, 2023; Beemer, et al., 2018; Li, Hong, & Craig, 2023; Talsma, Chapman, & Matthews, 2023). Refining the instrument and ensuring it stays relevant and accurate independent of the learner’s background or the type of the online learning environment depends on this exploration. The possible improvements could be changing the item language, including context-specific objects, or creating modular versions of the tool fit for many learning environments. These changes might improve the instrument’s usefulness in many educational environments, therefore benefiting academics and practitioners trying to properly support and evaluate online learner competencies. This study’s validation of the educational scale sheds light on important aspects of developing and refining measurement tools for complex learning constructs, such as Reflective Thinking, Self-Efficacy, SRL, Discussion, Task, and Exam. By thoroughly analysing factor loadings, the study reinforces the importance of strong construct validity to ensure that the scale accurately measures what it is intended to assess. The findings show that most items related to Reflective Thinking, Self-Efficacy, and SRL have moderate to high factor loadings, which confirm their strong representation within the scale. This suggests that the instrument is effective in capturing the cognitive and metacognitive processes essential for learning. However, some items were found to have low or negative loadings, indicating the need for careful revision. Refining these items – whether by rewording, modifying, or removing them – will help improve the scale’s accuracy and reliability. Making these adjustments will ensure that the instrument remains a valuable and dependable tool for assessing key aspects of learning.

This study suggests that things like age, field of study, and academic level can shape how students approach learning, particularly in terms of reflective thinking, self-efficacy, and SRL. Studying deeper into how these factors interact can make the tools we use more practical and useful. For example, older students may have stronger self-management skills due to their life and work experiences, while younger students may benefit from additional guidance. Similarly, students in different disciplines, such as science and the humanities, may exhibit varying levels of reflective thinking or confidence depending on the specific demands of their respective fields. How well students do in online learning also depends on how comfortable they are with the mental and technical side of it. Younger students often pick up technology more quickly, while older students may bring more life experience. Additionally, differences in how people prefer to learn – whether they prefer visuals, hands-on activities, or reading – can affect how much they enjoy and engage with online courses (Khalifeh, Noroozi, Farrokhnia, & Talaee, 2020; Syed, 2021).

The study focused on purposively selected postgraduate students taking online courses at the open and distance learning. While this group was carefully selected, the small sample size means the findings may not apply to all students, particularly those at different academic levels, in different types of schools, or from different cultural backgrounds. Future studies should include a more diverse group of participants – across different universities, disciplines, and teaching methods – so that the tool can be applied more broadly. Exploring these ideas across different institutions and cultures could also help us better understand how these learning processes work in different settings. One interesting thing about this study is that it used a single question to measure things like Discussion, Assignment, and Exam performance, and these questions performed perfectly. While this suggests that the tool works well, it also raises the question of whether this measure may be too simplistic. Future work could look at whether adding more questions or modifying this measure might give us a richer understanding of these concepts. Single-item assessments, although efficient and direct, may inadequately represent the multifaceted character of student engagement in discussions, task performance, and examination-related activities. The utilization of single-item indicators may constrain the exploration of variances in these structures, hence restricting the analytical depth. Future studies should investigate the creation of multi-item scales to offer a more refined evaluation of these variables, ensuring their complexity and variability are sufficiently captured. The use of supplementary indicators may improve the reliability and depth of assessment, resulting in a more thorough evaluation of student learning experiences.

Future studies should improve validation efforts by using bigger and more varied samples and by honing the evaluation of key components, hence extending the results of this work. Analyzing the interactions of these elements across several learning environments – including blended, hybrid, or traditional face-to-face settings – may help the instrument be more useful in many educational settings. Furthermore, longitudinal studies looking at the development of reflective thinking, self-efficacy, and SRL throughout time would provide important new perspectives on their continuing influence on student performance. Important studies could help to spot patterns, assess the effectiveness of interventions, and improve pedagogical approaches for developing important skills in distance and online learning settings.

Acknowledgments

The authors would like to express their sincere gratitude to the Institute for Research and Community Service (LPPM); the Dean and Vice Deans of the Faculty of Teacher Training and Education; the Director and Vice Directors of the Postgraduate School; and the Heads of Study Programs, lecturers, and students of the Basic Education Master’s Program at Universitas Terbuka, Indonesia. The authors are also grateful to the reviewers for their valuable comments, which helped improve the quality of this manuscript.

  1. Funding information: The research was fully funded by the Institute for Research and Community Service (LPPM), Universitas Terbuka, Indonesia.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript, consented to its submission to the journal, reviewed all the results, and approved the final version. AS and MS designed and conducted the experiments. AS, MP, and FA analysed the data and prepared both the initial and final versions of the manuscript.

  3. Conflict of interest: The authors state no conflict of interest.

  4. Ethical approval: This research involving human subjects has been conducted in accordance with all applicable national regulations and institutional policies.

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Received: 2024-04-22
Revised: 2025-03-16
Accepted: 2025-04-08
Published Online: 2025-05-07

© 2025 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/edu-2025-0076
Keywords for this article
educational assessment; higher education; online learning environments; open and distance education
Creative Commons
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