Abstract
The effective use of self-regulation strategies has been considered significant in online learning environments. It is known that learners must be supported in this context. Academic help-seeking (AHS), as one of the main self-regulated learning strategies, is associated with academic success. However, learners may avoid seeking help for cognitive, affective or social reasons. They might also be undecided about where to start when they need help. Therefore, external interventions are necessary to support learners in developing effective AHS skills. The purpose of this research was to examine the effect of prompts on fostering learners’ online AHS behaviour using learning analytics approaches. The research was conducted in an experimental design and included two separate experimental studies. The prompts used in the first and second studies focused on different factors that disrupted effective AHS processes. Learning analytics indicators were used as a proxy to understand the participants’ AHS behaviours in an online learning environment. The findings supported the idea that the prompts invited and guided students to relevant sources of help and fostered AHS behaviours in the online learning environment. Moreover, they contributed to the successful completion of learning tasks by up to 25%. The findings were discussed on the basis of the relevant literature, and suggestions for further research were provided.
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The datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.
References
Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia, 60(9), 662.
Azevedo, R., Johnson, A., Chauncey, A., & Burkett, C. (2010). Self-regulated learning with MetaTutor: Advancing the science of learning with MetaCognitive tools. New science of learning (pp. 225–247). Springer.
Bannert, M., & Reimann, P. (2011). Supporting self-regulated hypermedia learning through prompts. Instructional Science, 40(1), 193–211. https://doi.org/10.1007/s11251-011-9167-4
Berthold, K., Nückles, M., & Renkl, A. (2007). Do learning protocols support learning strategies and outcomes? The role of cognitive and metacognitive prompts. Learning and Instruction, 17(5), 564–577. https://doi.org/10.1016/j.learninstruc.2007.09.007
Butler, R., & Shibaz, L. (2008). Achievement goals for teaching as predictors of students’ perceptions of instructional practices and students’ help seeking and cheating. Learning and Instruction, 18(5), 453–467.
Calafiore, P., & Damianov, D. S. (2011). The effect of time spent online on student achievement in online economics and finance courses. The Journal of Economic Education, 42(3), 209–223.
Cappellini, M., Lewis, T., & Rivens Mompean, A. (2017). Learner autonomy and web 2.0. Equinox.
Cerezo, R., Sánchez-Santillán, M., Paule-Ruiz, M. P., & Núñez, J. C. (2016). Students’ LMS interaction patterns and their relationship with achievement: A case study in higher education. Computers & Education, 96, 42–54.
Chatti, M. A., Dyckhoff, A. L., Schroeder, U., & Thüs, H. (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning, 4(5–6), 318–331.
Chen, Y., Li, L., Wang, X., Li, Y., & Gao, F. (2018). Shyness and learning adjustment in senior high school students: Mediating roles of goal orientation and academic help seeking. Frontiers in Psychology, 9, 1757.
Chyr, W. L., Shen, P. D., Chiang, Y. C., Lin, J. B., & Tsai, C. W. (2017). Exploring the effects of online academic help-seeking and flipped learning on improving students’ learning. Journal of Educational Technology & Society, 20(3), 11–23.
Corrin, L., de Barba, P. G., & Bakharia, A. (2017). Using learning analytics to explore help-seeking learner profiles in MOOCs. Proceedings of the Seventh International Learning Analytics & Knowledge Conference.
Dabbagh, N., & Kitsantas, A. (2012). Personal learning environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. The Internet and Higher Education, 15(1), 3–8.
Damianov, D. S., Kupczynski, L., Calafiore, P., Damianova, E. P., Soydemir, G., & Gonzalez, E. (2009). Time spent online and student performance in online business courses: A multinomial logit analysis. Journal of Economics and Finance Education, 8(2), 11–22.
Davis, E. A. (2003). Prompting middle school science students for productive reflection: Generic and directed prompts. The Journal of the Learning Sciences, 12(1), 91–142.
Davis, N. L., Gough, M., & Taylor, L. L. (2019). Online teaching: Advantages, obstacles and tools for getting it right. Journal of Teaching in Travel & Tourism, 19(3), 256–263.
Devolder, A., van Braak, J., & Tondeur, J. (2012). Supporting self-regulated learning in computer-based learning environments: Systematic review of effects of scaffolding in the domain of science education. Journal of Computer Assisted Learning, 28(6), 557–573. https://doi.org/10.1111/j.1365-2729.2011.00476.x
Dong, A., Jong, M. S. Y., & King, R. B. (2020). How does prior knowledge influence learning engagement? The mediating roles of cognitive load and help-seeking. Frontiers in Psychology, 11, 591203.
Eric, Araka Elizaphan, Maina Rhoda, Gitonga Robert, Oboko (2020) Research trends in measurement and intervention tools for self-regulated learning for e-learning environments—systematic review (2008–2018) Abstract Research and Practice in Technology Enhanced Learning 15(1). https://doi.org/10.1186/s41039-020-00129-5
Firat, M. (2016). Determining the effects of LMS learning behaviors on academic achievement in a learning analytic perspective. Journal of Information Technology Education Research, 15, 75.
Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (Vol. 7). McGraw-hill.
Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64–71.
Giblin, J., & Stefaniak, J. (2021). Examining decision-making processes and heuristics in academic help-seeking and instructional environments. [Article] Techtrends, 65(1), 101–110. https://doi.org/10.1007/s11528-020-00556-7
Giblin, J., Stefaniak, J., Eckhoff, A., & Luo, T. (2021). An exploration of factors influencing the decision-making process and selection of academic help sources. Journal of Computing in Higher Education, 33(1), 1–18.
Guo, L. (2022). Using metacognitive prompts to enhance self-regulated learning and learning outcomes: A meta‐analysis of experimental studies in computer‐based learning environments. Journal of Computer Assisted Learning, 38(3), 811–832.
Henrie, C. R., Bodily, R., Larsen, R., & Graham, C. R. (2017). Exploring the potential of LMS log data as a proxy measure of student engagement. Journal of Computing in Higher Education, 30(2), 344–362. https://doi.org/10.1007/s12528-017-9161-1
Ifenthaler, D. (2012). Determining the effectiveness of prompts for self-regulated learning in problem-solving scenarios. Journal of Educational Technology & Society, 15(1), 38–52.
Järvelä, S. (2011). How does help seeking help?–New prospects in a variety of contexts. Learning and Instruction, 21(2), 297–299.
Karabenick, S. (1998). Strategic help seeking: Implications for knowledge acquisition. Erlbaum. 10.9781410602701.
Karabenick, S. A., & Berger, J.-L. (2013). Help seeking as a self-regulated learning strategy. In H. Bembenutty, T. J. Cleary, & A. Kitsantas (Eds.), Applications of self-regulated learning across diverse disciplines: A tribute to Barry J. Zimmerman (pp. 237–261). IAP Information Age Publishing.
Karabenick, S. A., & Dembo, M. H. (2011). Understanding and facilitating self-regulated help seeking. New Directions for Teaching and Learning, 2011(126), 33–43.
Karabenick, S. A., & Gonida, E. N. (2017). Academic help seeking as a self-regulated learning strategy: Current issues, future directions. Handbook of self-regulation of learning and performance (pp. 421–433). Routledge.
Karabenick, S. A., & Sharma, R. (1994). Perceived teacher support of student questioning in the college classroom: Its relation to student characteristics and role in the classroom questioning process. Journal of Educational Psychology, 86(1), 90.
Kew, S. N., & Tasir, Z. (2022). Learning Analytics in Online Learning Environment: A Systematic Review on the Focuses and the Types of Student-Related Analytics Data. Technology, Knowledge and Learning, 27(2), 405–427.
Kim, H. Y. (2017). Statistical notes for clinical researchers: Chi-squared test and Fisher’s exact test. Restorative Dentistry & Endodontics, 42(2), 152–155.
Kim, D., Yoon, M., Jo, I. H., & Branch, R. M. (2018). Learning analytics to support self-regulated learning in asynchronous online courses: A case study at a women’s university in South Korea. Computers & Education, 127, 233–251. https://doi.org/10.1016/j.compedu.2018.08.023
King, A. (1992). Facilitating elaborative learning through guided student-generated questioning. Educational Psychologist, 27(1), 111–126.
Kizilcec, R. F., Perez-Sanagustin, M., & Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in massive Open Online Courses. Computers & Education, 104, 18–33. https://doi.org/10.1016/j.compedu.2016.10.001
Kwan, A. C., Tang, K. C., & Chan, K. (2019). Impacts of online academic help-seeking behaviors on undergraduate student self-learning. 2019 IEEE International Conference on Engineering, Technology and Education (TALE).
Lodge, J. M., Panadero, E., Broadbent, J., & de Barba, P. G. (2018). Supporting self-regulated learning with learning analytics. In Learning analytics in the classroom (pp. 45–55). Routledge.
Lehmann, T., Hähnlein, I., & Ifenthaler, D. (2014). Cognitive, metacognitive and motivational perspectives on preflection in self-regulated online learning. Computers in Human Behavior, 32, 313–323.
Ludwig, C., & Tassinari, M. G. (2023). Foreign language learner autonomy in online learning environments: the teachers’ perspectives. Innovation in Language Learning and Teaching, 17(2), 217–234. https://doi.org/10.1080/17501229.2021.2012476
Martín-Arbós, S., Castarlenas, E., & Dueñas, J. M. (2021). Help-seeking in an academic context: A systematic review. Sustainability, 13(8). https://doi.org/10.3390/su13084460
Matcha, W., Gašević, D., & Pardo, A. (2019). A systematic review of empirical studies on learning analytics dashboards: A self-regulated learning perspective. IEEE Transactions on Learning Technologies, 13(2), 226–245.
Mayweg-Paus, E., Zimmermann, M., Le, N. T., & Pinkwart, N. (2021). A review of technologies for collaborative online information seeking: On the contribution of collaborative argumentation. Education and Information Technologies, 26(2), 2053–2089.
Moos, D. C., & Azevedo, R. (2009). Learning with computer-based learning environments: A literature review of computer self-efficacy. Review of Educational Research, 79(2), 576–600.
Nelson-Le Gall, S. (1981). Help-seeking: An understudied problem-solving skill in children. Developmental Review, 1(3), 224–246.
Newman, R. (1991). Goals and self-regulated learning: What motivates children to seek academic help. Advances in Motivation and Achievement, 7, 151–183.
Newman, R. S. (1994). Adaptive help seeking: A strategy of self-regulated learning. Self-regulation of learning and performance: Issues and educational applications, 283–301.
Newman, R. S. (2002). How self-regulated Learners cope with academic difficulty: The role of adaptive help seeking. Theory Into Practice, 41(2), 132–138. https://doi.org/10.1207/s15430421tip4102_10
Newman, R. S. (2012). The motivational role of adaptive help seeking in self-regulated learning. Motivation and self-regulated learning (pp. 315–337). Routledge.
Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, 422.
Panadero, E., & Alonso-Tapia, J. (2014). Cómo autorregulan nuestros alumnos? Modelo de Zimmerman sobre estrategias de aprendizaje. Anales de Psicología, 30(2). https://doi.org/10.6018/analesps.30.2.167221
Papamitsiou, Z., & Economides, A. A. (2019). Exploring autonomous learning capacity from a self-regulated learning perspective using learning analytics. British Journal of Educational Technology, 50(6), 3138–3155.
Puustinen, M., & Rouet, J. F. (2009). Learning with new technologies: Help seeking and information searching revisited. Computers & Education, 53(4), 1014–1019.
Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers & Education, 144, 103701.
Ronald, Pérez-Álvarez Jorge, Maldonado-Mahauad Mar, Pérez-Sanagustín Viktoria, Pammer-Schindler Mar, Pérez-Sanagustín Hendrik, Drachsler Raymond, Elferink Maren, Scheffel (2018) Lifelong Technology-Enhanced Learning 13th European Conference on Technology Enhanced Learning EC-TEL 2018 Leeds UK September 3-5 2018 Proceedings Tools to Support Self-Regulated Learning in Online Environments: Literature Review Springer International Publishing Cham 16-30
Roll, I., Aleven, V., McLaren, B. M., & Koedinger, K. R. (2011). Improving students’ help-seeking skills using metacognitive feedback in an intelligent tutoring system. Learning and Instruction, 21(2), 267–280.
Ryan, A. M., & Pintrich, P. R. (1997). Should I ask for help?“ the role of motivation and attitudes in adolescents’ help seeking in math class. Journal of Educational Psychology, 89(2), 329.
Ryan, A. M., & Shim, S. S. (2012). Changes in help seeking from peers during early adolescence: Associations with changes in achievement and perceptions of teachers. Journal of Educational Psychology, 104(4), 1122–1134. https://doi.org/10.1037/a0027696
Ryan, A. M., Pintrich, P. R., & Midgley, C. (2001). Avoiding seeking help in the classroom: Who and why? Educational Psychology Review, 13(2), 93–114.
Schumacher, C., & Ifenthaler, D. (2021). Investigating prompts for supporting students’ self-regulation – A remaining challenge for learning analytics approaches? The Internet and higher education, 49. https://doi.org/10.1016/j.iheduc.2020.100791
Sapiro, B., Shpiegel, S., Ramirez Quiroz, S., Ventola, M., Nwankwo, O. H., & Munyereyi, T. (2023). “It’s Just Hard Reaching Out”: Factors Affecting Help-Seeking Behaviors among Independent College Students. Journal of College Student Retention: Research, Theory & Practice, 0(0). https://doi.org/10.1177/15210251231159642
Schunk, D. H., & Zimmerman, B. J. (2007). Influencing children’s self-efficacy and self-regulation of reading and writing through modeling. Reading & Writing Quarterly, 23(1), 7–25.
Schunk, D. H., & Zimmerman, B. J. (2013). Self-regulation and learning. In W. M. Reynolds, G. E. Miller, & I. B. Weiner (Eds.), Handbook of psychology: Educational psychology (pp. 45–68). John Wiley & Sons Inc.
Schworm, S., & Gruber, H. (2012). e-Learning in universities: Supporting help-seeking processes by instructional prompts. British Journal of Educational Technology, 43(2), 272–281. https://doi.org/10.1111/j.1467-8535.2011.01176.x
Seif, M., Rastegar, A., Talebi, S., Yadegar, M., & Qaeedi, R. (2020). Presenting causal model of goals orientation dimensions relations and academic help seeking: The role of academic engagement and self-efficiency. Journal of School Psychology, 9(3), 139–161.
Selwyn, N., & Gašević, D. (2020). The datafication of higher education: Discussing the promises and problems. Teaching in Higher Education, 25(4), 527–540.
Veenman, M. V. J. (2007). The assessment and instruction of self-regulation in computer-based environments: A discussion. Metacognition and Learning, 2(2–3), 177–183. https://doi.org/10.1007/s11409-007-9017-6
Veletsianos, G., Reich, J., & Pasquini, L. A. (2016). The life between big data log events: Learners’ strategies to overcome challenges in MOOCs. AERA Open, 2(3), 2332858416657002.
Vilkova, K., & Shcheglova, I. (2021). Deconstructing self-regulated learning in MOOCs: In search of help-seeking mechanisms. Education and Information Technologies, 26(1), 17–33.
Wirth, J. (2009). Promoting self-regulated learning through prompts. Zeitschrift für Pädagogische Psychologie, 23(2), 91–94.
Witherspoon, A. M., & Azevedo, R. (2009). 17 self-regulated learning with Hypermedia. Handbook of metacognition in education, 2001, 319.
Wong, J., Baars, M., de Koning, B. B., & Paas, F. (2021). Examining the use of prompts to facilitate self-regulated learning in massive Open Online Courses. Computers in Human Behavior, 115. https://doi.org/10.1016/j.chb.2020.106596
Zheng, B., & Zhang, Y. (2020). Self-regulated learning: The effect on medical student learning outcomes in a flipped classroom environment. BMC Medical Education, 20(1), 1–7.
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166–183.
Zimmerman, B. J., & Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. Handbook of metacognition in education (pp. 311–328). Routledge.
Zimmerman, B. J., & Pons, M. M. (2016). Development of a structured interview for assessing Student Use of Self-Regulated learning strategies. American Educational Research Journal, 23(4), 614–628. https://doi.org/10.3102/00028312023004614
Zimmerman, B. J., & Pons, M. M. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American Educational Research Journal, 23(4), 614–628.
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Appendix 1
Appendix 1
Descriptive statistics for dependent variables
Study I | Experimental Group | Control Group | ||||||||||||||
N | Mean | Standard Deviation | Min. | Max. | Median | Shapiro-Wilk Sig. | N | Mean | Standard Deviation | Min | Max. | Median | Shapiro-Wilk Sig. | |||
AssignmentView | 19 | 42.68 | 18.856 | 6 | 84 | 42.00 | 0.998 | AssignmentView | 20 | 44.30 | 52.392 | 8 | 259 | 33.50 | 0.000 | |
Time Spent | 19 | 185.47 | 192.371 | 38 | 935 | 139.00 | 0.000 | Time Spent | 20 | 139.35 | 111.309 | 32 | 517 | 100.00 | 0.000 | |
Session | 19 | 36.16 | 94.124 | 5 | 424 | 16.00 | 0.000 | Session | 20 | 15.55 | 9.539 | 5 | 41 | 13.00 | 0.019 | |
View Discussion | 19 | 662.16 | 2244.799 | 0 | 9736 | 28.00 | 0.000 | View Discussion | 20 | 275.35 | 797.772 | 0 | 3469 | 15.50 | 0.000 | |
Start Discussion | 19 | 1.89 | 3.604 | 0 | 14 | 0.00 | 0.000 | Start Discussion | 20 | 2.15 | 3.717 | 0 | 15 | 0.00 | 0.000 | |
AccessResource | 19 | 12.53 | 15.200 | 1 | 49 | 6.00 | 0.000 | AccessResource | 20 | 11.70 | 13.982 | 1 | 52 | 5.50 | 0.000 | |
Access oth. Res. | 19 | 2.21 | 2.226 | 0 | 7 | 1.00 | 0.008 | Access oth. Res. | 20 | 1.80 | 1.704 | 0 | 6 | 1.50 | 0.017 | |
Access Module | 19 | 105.47 | 152.340 | 22 | 709 | 66.00 | 0.000 | Access Module | 20 | 80.65 | 72.434 | 10 | 332 | 62.50 | 0.000 | |
Access Videos | 19 | 20.74 | 9.550 | 12 | 52 | 20.00 | 0.001 | Access Videos | 20 | 21.65 | 12.036 | 3 | 48 | 20.00 | 0.443 | |
Study II | AssignmentView | 19 | 47.26 | 25.987 | 16 | 124 | 38.00 | 0.006 | AssignmentView | 20 | 48.90 | 99.038 | 0 | 465 | 30.00 | 0.000 |
Time Spent | 19 | 173.74 | 144.242 | 10 | 656 | 124 | 0.001 | Time Spent | 20 | 103.25 | 83.404 | 1 | 356 | 71.50 | 0.003 | |
Session | 19 | 37.37 | 94.201 | 3 | 425 | 16.00 | 0.000 | Session | 20 | 13.90 | 10.346 | 1 | 41 | 11.50 | 0.037 | |
View Discussion | 19 | 761.84 | 2646.918 | 0 | 11488 | 11.00 | 0.000 | View Discussion | 20 | 147.35 | 285.091 | 0 | 930 | 10.00 | 0.000 | |
Start Discussion | 19 | 2.16 | 3.500 | 0 | 11 | 0.00 | 0.000 | Start Discussion | 20 | 1.30 | 2.618 | 0 | 10 | 0.00 | 0.000 | |
AccessResource | 19 | 21.42 | 18.798 | 1 | 67 | 17.00 | 0.008 | AccessResource | 20 | 17.55 | 18.869 | 0 | 71 | 10.50 | 0.000 | |
Access oth. Res. | 19 | 6.16 | 4.764 | 0 | 16 | 6.00 | 0.303 | Access oth. Res. | 20 | 5.05 | 5.176 | 0 | 18 | 4.00 | 0.001 | |
Access Module | 19 | 109.68 | 137.648 | 17 | 645 | 76.00 | 0.000 | Access Module | 20 | 80.20 | 105.827 | 1 | 492 | 47.00 | 0.000 | |
Access Videos | 19 | 5.79 | 4.417 | 0 | 14 | 6.00 | 0.198 | Access Videos | 20 | 5.60 | 4.477 | 0 | 17 | 5.50 | 0.154 |
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Önder, A., Akçapınar, G. Investigating the effect of prompts on learners’ academic help-seeking behaviours on the basis of learning analytics. Educ Inf Technol 28, 16909–16934 (2023). https://doi.org/10.1007/s10639-023-11872-9
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DOI: https://doi.org/10.1007/s10639-023-11872-9