What changes, and for whom? A study of the impact of learning analytics-based process feedback in a large course
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GenAI has the potential to provide timely, specific, and constructive feedback.
“Another promise of GenAI in supporting human learning is its potential to provide timely, specific, and constructive feedback, a key element of high-quality instruction and essential for effective learning [34][35][36].”
From Promises and challenges of generative artificial intelligence for human learning (2024) · cites this paper as [35]
Analyzing feedback data helped instructors pinpoint gaps in students' procedural skills.
“Studies [135,136] demonstrated how analyzing feedback data helped instructors pinpoint gaps in students' procedural skills.”
From Formative assessment and feedback in medical education: A practical guide: AMEE Guide No. 189 (2026) · cites this paper as [135]
Identification of gaps in procedural skills led to more targeted interventions and improved learning outcomes.
“This identification led to more targeted interventions and improved learning outcomes, ensuring that students received the support they needed to address specific areas of difficulty.”
From Formative assessment and feedback in medical education: A practical guide: AMEE Guide No. 189 (2026) · cites this paper as [135]
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Promises and challenges of generative artificial intelligence for human learning
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Self-citationAutomatic feedback in online learning environments: A systematic literature review
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Self-citationEffects of real-time analytics-based personalized scaffolds on students’ self-regulated learning
Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., Rakovic, M., Molenaar, I., Moore, J., & Gašević, D. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107547 · Cited by 198 · see citing works
“…by process analyses, as theorized by SRL models (e.g., Zimmerman, 2002), such as first analyzing the task, monitoring while performing various cognitive activities, and evaluating learning (Bannert, Reimann, & Sonnenberg, 2014; Lim et al., 2021; Paans, Molenaar, Segers, & Verhoeven, 2019).”
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“In other cases, some researchers used focus groups (Balavijendran & Burnie, 2018; Lim et al., 2021; Lim et al., 2020), observations of facial expressions (Bouchet et al.”
BackgroundResultInfluentialYan, L., Martínez‐Maldonado, R., & Gašević, D. (2024) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3636555.3636856 · Cited by 154 · see citing works
“Similar opportunities may also apply to the illustration and presentation of LA. Prior LA research has demonstrated the benefits of data-driven personalised feedback in improving learners’ academic achievement [57, 75].”
BackgroundSelf-citationLiu, Z.-M., Hwang, G.-J., Chen, C.-Q., Chen, X.-D., & Ye, X.-D. (2026) · Computer Assisted Language Learning · doi:10.1080/09588221.2024.2389923 · Cited by 115 · see citing works
“However, existing scaffolds often fail to adequately account for the dynamic nature of SRL processes, lacking adapt-ability and personalization (Lim et al., 2021; Zheng et al., 2023).”
Kew, S. N., & Tasir, Z. (2021) · Technology Knowledge and Learning · doi:10.1007/s10758-021-09541-2 · Cited by 116 · see citing works
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“These findings are consistent with those reported by The findings relating to the provision of LA-based feedback are consistent with those reported by Lim et al. (2021); that is, using the LA-based feedback in a course that implemented the BL setting can improve students’ learning achievements.”
BackgroundResultLim, L.-A., Dawson, S., Gašević, D., Joksimović, S., Pardo, A., Fudge, A., & Gentili, S. (2021) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2020.1782831 · Cited by 113 · see citing works
“A key focus in learning analytics research is facilitating ‘ the provision of automated, scaled and real-time feedback to learners ’ (Pardo et al. 2019, 167).”
BackgroundInfluentialSelf-citationAnalytics of Learning Strategies: Role of Course Design and Delivery Modality
Matcha, W., Gašević, D., Uzir, N. A., Jovanović, J., Pardo, A., Lim, L.-A., Maldonado‐Mahauad, J., Gentili, S., Pérez‐Sanagustín, M., & Tsai, Y. (2020) · Journal of Learning Analytics · doi:10.18608/jla.2020.72.3 · Cited by 81 · see citing works
“Previous studies showed that by customizing the feedback to suit the given learning situation, learners could be provided with help for improving their academic performance (Matcha, Gašević, Ahmad Uzir, Jovanović, & Pardo, 2019; Lim et al., 2019).”
BackgroundSelf-citationLearning analytics for online game-Based learning: a systematic literature review
Banihashem, S. K., Dehghanzadeh, H., Clark, D. B., Noroozi, O., & Biemans, H. J. A. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2255301 · Cited by 92 · see citing works
“LA assists learners with adaptive learning by providing real-time feedback and re fl ections on the learning process (Lim et al. 2021).”
Gašević, D., Greiff, S., & Shaffer, D. W. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107304 · Cited by 82 · see citing works
“The use of learning analytics has also shown its potential to enhance both student retention (Arnold & Pistilli, 2012) and quality of feedback (Lim et al., 2021; Pardo, 2018), and to inform teaching practice (Martínez-Maldonado et al., 2022).”
BackgroundSelf-citationZheng, L., Niu, J., & Zhong, L. (2021) · British Journal of Educational Technology · doi:10.1111/bjet.13156 · Cited by 78 · see citing works
Student Opinions About Personalized Recommendation and Feedback Based on Learning Analytics
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Students’ sense-making of personalised feedback based on learning analytics
Lim, L.-A., Dawson, S., Gašević, D., Joksimović, S., Fudge, A., Pardo, A., & Gentili, S. (2020) · Australasian Journal of Educational Technology · doi:10.14742/ajet.6370 · Cited by 66 · see citing works
“Most recent empirical studies have indicated that personalised, LA-based feedback yields observable, positive benefits for students’ SRL in terms of learning strategies and performance (Lim et al., 2019; Matcha et al., 2019), as well as time management (Ahmad Uzir et al., 2019).”
BackgroundSelf-citationCai, Z., Gui, Y., Mao, P., Wang, Z., Hao, X., Fan, X., & Tai, R. H. (2023) · Educational Research Review · doi:10.1016/j.edurev.2023.100521 · Cited by 76 · see citing works
Buckingham Shum, S., Lim, L.-A., Boud, D., Bearman, M., & Dawson, P. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00410-9 · Cited by 77 · see citing works
“Finally, there is emerging evidence that learners’ attributes have some influence on their feedback literacy, such as prior academic performance (Lim et al., 2021a), self-efficacy and baseline self-regulation (Tsai et al., 2021), or performance goals (Brown et al., 2019).”
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“External feedback can assist learners in adapting, selecting as well as utilizing regulatory strategies, thereby stimulating internal feedback processes and enhancing SRL skills (Lim et al., 2021).”
BackgroundData frontiers and frontiers of power in (higher) education: a view of/from the Global South
Prinsloo, P. (2020) · Teaching in Higher Education · doi:10.1080/13562517.2020.1723537 · Cited by 50 · see citing works
Lim, L.-A., Gasevic, D., Matcha, W., Ahmad Uzir, N., & Dawson, S. (2021) · LAK21: 11th International Learning Analytics and Knowledge Conference · doi:10.1145/3448139.3448174 · Cited by 47 · see citing works
“To date, studies have found benefits of this novel approach to feedback on students’ satisfaction with feedback [25] and course performance [15, 25].”
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Bauer, E., Sailer, M., Niklas, F., Greiff, S., Sarbu‐Rothsching, S., Zottmann, J., Kiesewetter, J., Stadler, M. J., Fischer, M. R., Seidel, T., et al. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13123 · Cited by 45 · see citing works
Valle, N., Antonenko, P., do Valle, D. R., Dawson, K., Huggins‐Manley, A. C., & Baiser, B. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104288 · Cited by 47 · see citing works
Alalawi, K., Athauda, R., Chiong, R., & Renner, I. W. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12923-5 · Cited by 64 · see citing works
“…PSM attempts to remove bias by identifying control and treatment groups from the study cohort in such a way that students had a similar probability of being assigned to the control and treatment group based on a set of baseline characteristic variables (Lim et al., 2021 ; Mojarad et al., 2018 ).”
Analytics of learning strategies
Matcha, W., Gašević, D., Jovanović, J., Uzir, N. A., Oliver, C., Murray, A. D., & Gašević, D. (2020) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3375462.3375534 · Cited by 47 · see citing works
“on the choice of learning strategies [44, 21], student satisfaction with feedback [49], and academic performance have already been reported in the literature [35].”
BackgroundSelf-citationUrbina, S., Villatoro, S., & Salinas, J. (2021) · Sustainability · doi:10.3390/su13137281 · Cited by 43 · see citing works
Learning analytics in higher education – Stakeholders, strategy and scale
Gašević, D., Tsai, Y., & Drachsler, H. (2021) · The Internet and Higher Education · doi:10.1016/j.iheduc.2021.100833 · Cited by 43 · see citing works
Self-citationStudent appreciation of data-driven feedback: A pilot study on OnTask
Tsai, Y.-S., Mello, R. F., Jovanović, J., & Gašević, D. (2021) · LAK21: 11th International Learning Analytics and Knowledge Conference · doi:10.1145/3448139.3448212 · Cited by 41 · see citing works
“So far, existing literature about OnTask has looked at student satisfaction [22], student experience through qualitative insights [16], and the association between feedback experience and learning outcomes [17].”
BackgroundEarly morning university classes are associated with impaired sleep and academic performance
Yeo, S. C., Lai, C. K., Tan, J., Lim, S., Chandramoghan, Y., Tan, T. K., & Gooley, J. J. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01531-x · Cited by 53 · see citing works
Mousavi, A., Schmidt, M., Squires, V., & Wilson, K. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00210-6 · Cited by 41 · see citing works
“Lim and colleagues looked at the effect of OnTask ’ s personalized feedback administration on student self regulated learning and academic performance, finding positive effects of both provided by the intervention (Lim et al. 2019).”
BackgroundMethodInfluentialIraj, H., Fudge, A. L., Khan, H., Faulkner, M., Pardo, A., & Kovanović, V. (2021) · Journal of Learning Analytics · doi:10.18608/jla.2021.7184 · Cited by 40 · see citing works
“…feedback systems opened new opportunities for providing feedback to students and have proved to be effective for engaging students (Dawson et al., 2018; Lim et al., 2019), boosting students’ satisfaction (Pardo et al., 2019), and improving outcomes (Dawson et al., 2018; Pardo et al., 2019).”
BackgroundResultInfluentialSelf-citationUnderstanding students' engagement with personalised feedback messages
Iraj, H., Fudge, A. L., Faulkner, M., Pardo, A., & Kovanović, V. (2020) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3375462.3375527 · Cited by 36 · see citing works
“This might be explained by the point that acting on feedback messages nudged students to engage early with the course and study regularly throughout the semester [41].”
BackgroundInfluentialSelf-citationFormative assessment and feedback in medical education: A practical guide: AMEE Guide No. 189
Lipnevich, A. A., Mattern, K., & Feddock, C. (2026) · Medical Teacher · doi:10.1080/0142159x.2025.2569623 · Cited by 37 · see citing works
Bauer, E., Richters, C., Pickal, A. J., Klippert, M., Sailer, M., & Stadler, M. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.13609 · Cited by 33 · see citing works
Supporting actionable intelligence
Jovanović, J., Dawson, S., Joksimovíc, S., & Siemens, G. (2020) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3375462.3375474 · Cited by 31 · see citing works
“…to feedback provision at scale, such as those implemented in Student Relationship Engagement System, SRES [21] and the OnTask tool [29], allow course instructors to offer personalised process-oriented feedback to students [20], thus supporting students’ learning even in large-scale courses.”
MethodSelf-citationDart, S., & Spratt, B. (2020) · Student Success · doi:10.5204/ssj.1543 · Cited by 31 · see citing works
“One technology-based approach to student support is personalised emails, where analytical insights from online engagement and course performance are used to develop messages customised to individuals (Lim et al., 2019).”
BackgroundMethodResultInfluentialCausal Inference and Bias in Learning Analytics
Weidlich, J., Gašević, D., & Drachsler, H. (2022) · Journal of Learning Analytics · doi:10.18608/jla.2022.7577 · Cited by 27 · see citing works
“A widely used method of this approach is propensity score matching (Rosenbaum & Rubin, 1983; Austin, 2011), which has also been employed in the LA literature (Lim et al., 2021).”
MethodSelf-citationNicolay, B., Krieger, F., Stadler, M. J., Gobert, J. D., & Greiff, S. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106594 · Cited by 26 · see citing works
“Generally, such thorough investigations of performance-related data provide a deep insight into how students approach complex problems, and are frequently performed in the context of learning analytics (Kim, Yoon, Jo, & Branch, 2018; Lim et al., 2019; Nistor & Hernández-Garcíac, 2018).”
Analyzing the Efficacy of ECoach in Supporting Gateway Course Success Through Tailored Support
Matz, R. L., Schulz, K. W., Hanley, E., Derry, H. A., Hayward, B., Koester, B. P., Hayward, C., & McKay, T. A. (2021) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3448139.3448160 · Cited by 23 · see citing works
“Reflecting on the alignment (or lack thereof) between students’ intended performance, preparatory strategies, and actual exam performance is a key component of self-regulated learning behavior [7], which has been shown to help students process their learning and effort regulation [28] and specifically in similar intel…”
BackgroundWang, Y., Gao, C.-L., & Ye, X. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12238-x · Cited by 22 · see citing works
“…methodologies, researchers could analyze and forecast students’ academic performance, and this in-depth analysis allows instructors or automated systems to craft learner-centric instruction tailored to individual needs (as evidenced by Lim et al., 2021; Şahin, 2023; Shabani & Eshaghian, 2014).”
Hu, J., & Zhang, Y. (2024) · Learning and Instruction · doi:10.1016/j.learninstruc.2024.101874 · Cited by 29 · see citing works
Hadwin, A. F. (2019) · Learning and Instruction · doi:10.1016/j.learninstruc.2019.101287 · Cited by 19 · see citing works
Feedback literacy matters: unlocking the potential of learning analytics-based feedback
Tepgeç, M., Heil, J., & Ifenthaler, D. (2024) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2024.2367587 · Cited by 18 · see citing works
“…feedback systems, which provide richer data and more targeted insights for potentially more effective learning outcomes, strengthens the long-established significance of feedback in shaping the learning process (Pardo et al. 2019; Lim et al. 2021; Ifenthaler, Schumacher, and Kuzilek 2023).”
Scaffolding Feedback Literacy: Designing a Feedback Analytics Tool with Students
Jin, F. J.-Y., Maheshi, B., Martínez‐Maldonado, R., Gašević, D., & Tsai, Y. (2024) · Journal of Learning Analytics · doi:10.18608/jla.2024.8339 · Cited by 18 · see citing works
“The themes of feedback characteristics (Ryan et al., 2023; Hattie & Timperley, 2007; Lim, Dawson, et al., 2021), agent characteristics (Jin et al., 2022), and learning design (Jin et al., 2022) were used to analyze additional causes of challenges perceived by students in the feedback process.”
Self-citationFeedback for student learning in higher education
Carless, D. R. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-818630-5.14066-7 · Cited by 18 · see citing works
Lewis, S., Heath, G., Lim, L., & Roberts, R. (2021) · Student Success · doi:10.5204/ssj.1623 · Cited by 17 · see citing works
“These findings of different online activity patterns and increased academic performance provide further evidence of the impact of personalised feedback previously demonstrated by other researchers in this field (e.g., Lim et al., 2019; Pardo et al. 2017b).”
BackgroundSelf-citationQi, X., Sun, G., & Yue, L. (2023) · Sustainability · doi:10.3390/su151612562 · Cited by 17 · see citing works
“Align course features with Feedback message details [21].”
BackgroundMcCarthy, K. S., Crossley, S. A., Meyers, K., Boser, U., Allen, L. K., Chaudhri, V. K., Collins‐Thompson, K., D’Mello, S. K., Choudhury, M. D., Garg, K., et al. (2022) · Technology Mind and Behavior · doi:10.1037/tmb0000063 · Cited by 17 · see citing works
Liu, Y., Wang, W., & Xu, E. (2025) · SAGE Open · doi:10.1177/21582440251336707 · Cited by 15 · see citing works
Chen, A., Lian, J., Kuang, X., & Jia, J. (2025) · The Internet and Higher Education · doi:10.1016/j.iheduc.2025.101054 · Cited by 18 · see citing works
Ceallaigh, T. J. Ó., O’ Brien, E., Tømte, C., Kulaksız, T., & Connolly, C. (2025) · European Journal of Teacher Education · doi:10.1080/02619768.2025.2563696 · Cited by 14 · see citing works
“It also offers timely, specific, and constructive feedback, an essential component of effective instruction (L. A. Lim et al. 2021; Pardo et al. 2019).”
A feedback model applied in a ubiquitous microlearning environment using SECA rules
Tabares, M. S., Vallejo, P., Montoya, A., & Correa, D. (2022) · Journal of Computing in Higher Education · doi:10.1007/s12528-021-09306-x · Cited by 18 · see citing works
“According to Lim et al. (2019), “a challenge for contemporary educators is how to provide feedback to all students in large courses in a personalized, timely and instructive manner.””
BackgroundLearning Analytics in Higher Education
Stokes, J., & Fudge, A. L. (2023) · doi:10.1093/obo/9780199756810-0297 · Cited by 13 · see citing works
Brass, T., Kennedy, J., Gabriel, F. C., Neill, B., Devis, D., & Leonard, S. N. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1173099 · Cited by 12 · see citing works
Dever, D. A., Wiedbusch, M. D., Romero, S. M., Smith, K., Patel, M., Sonnenfeld, N. A., Lester, J. C., & Azevedo, R. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1280566 · Cited by 12 · see citing works
Kia, F. S., Pardo, A., Dawson, S., & O'Brien, H. L. (2022) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2022.2139351 · Cited by 11 · see citing works
“However, there are several studies that have provided such insight at the course level with very encouraging results, as shown by lim et al. (2021b). A further limitation of the study was that the tool was available for instructor use on a course-by-course basis, preventing us from examining the impact of its use at t…”
ResultSelf-citationTechnology-Enhanced Feedback System Usability in the Context of Self-Regulation Promotion
Žerovnik, A. (2024) · Education Sciences · doi:10.3390/educsci14090948 · Cited by 23 · see citing works
Jung, Y., & Wise, A. F. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105280 · Cited by 11 · see citing works
Yang, Y. P., & Song, Y. (2022) · Journal of Computers in Education · doi:10.1007/s40692-022-00251-x · Cited by 10 · see citing works
Content-Focused Formative Feedback Combining Achievement, Qualitative and Learning Analytics Data
Martínez, M. C., Serra, R., Sundaramoorthy, P., Booij, T. B. N., Vertegaal, C. J. C., Bounik, Z., Hastenberg, K. A. P. V., & Bentum, M. (2023) · Education Sciences · doi:10.3390/educsci13101014 · Cited by 10 · see citing works
“[35] explored the impact of LA-based automatic feedback on student self-regulation and performance in a large undergraduate course.”
BackgroundGenerating actionable predictions regarding MOOC learners’ engagement in peer reviews
Er, E., Gómez-Sánchez, E., Bote-Lorenzo, M., Dimitriadis, Y., & Asensio-Pérez, J. (2019) · Behavior and Information Technology · doi:10.1080/0144929x.2019.1669222 · Cited by 12 · see citing works
Quadir, B., Chang, M., & Yang, J. C. (2021) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2021.100034 · Cited by 9 · see citing works
Merikko, J., Ng, K., Saqr, M., & Ihantola, P. (2022) · IEEE Access · doi:10.1109/access.2022.3207274 · Cited by 9 · see citing works
“Receiving personalized feedback with this approach has 73 been associated with a positive impact on student percep74 tion of feedback quality [10] and higher academic achieve75 ment [12].”
BackgroundPsathas, G., Tegos, S. D., Demetriadis, S., & Tsiatsos, Τ. (2023) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-023-09394-0 · Cited by 8 · see citing works
“According to Lim et al. (2019), individualized support based on LA leads to better learning outcomes.”
BackgroundTechnology-enhanced Learning and Learning Analytics for personalized STEM learning: A scoping review
Qushem, U. B., Christopoulos, A., Kaliisa, R., Khalil, M., Salakoski, T., & Laakso, M. (2025) · International Journal of Educational Research · doi:10.1016/j.ijer.2025.102827 · Cited by 12 · see citing works
Kyne, S. H., Lee, M. M. H., & Reyes, C. T. (2023) · Chemistry Education Research and Practice · doi:10.1039/d3rp00032j · Cited by 8 · see citing works
SECA: A Feedback Rules Model in a Ubiquitous Microlearning Context
Tabares, M. S., Vallejo, P., Montoya, A., Sanchez, J., & Correa, D. (2021) · International Conference on Data Science, E-Learning and Information Systems (DATA) · doi:10.1145/3460620.3460745 · Cited by 8 · see citing works
“[Lim et al. 2019], “a challenge for contemporary educators is how to provide feedback to all students in large courses in a personalised, timely and instructive manner.”
BackgroundPrediction of student performance in blended learning by utilizing learning analytics data
Ozerova, G. P., & Федоровна, П. Г. (2019) · Science for Education Today · doi:10.15293/2658-6762.1906.05 · Cited by 8 · see citing works
Establishing Trustworthy Artificial Intelligence in Automated FeedbackPreprint
Lin, J., Sha, L., Li, Y., Gašević, D., & Chen, G. (2022) · doi:10.35542/osf.io/5efxn · Cited by 8 · see citing works
Self-citationHu, Y.-H., Liao, B.-K., & Hsieh, C.-L. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2023.2277741 · Cited by 7 · see citing works
“LADs serve as e ff ective learning sca ff olds for learners (Lim et al., 2021) and have been designed to support SRL (Matcha et al., 2020; Siemens & Long, 2011).”
Ma’arif, M. (2020) · JURNAL PAJAR (Pendidikan dan Pengajaran) · doi:10.33578/pjr.v4i1.7894 · Cited by 7 · see citing works
Halder, D., & Panda, S. (2026) · Smart Learning Environments · doi:10.1186/s40561-025-00428-8 · Cited by 13 · see citing works
“Continuous feedback on readiness, self-efficacy, and persistence sustains autonomy and PL (Sáiz et al., 2020; Lim et al., 2021).”
A Meta-Analysis of the Impact of Feedback Timing on Learning Outcomes in Computer-Assisted Learning
Kandemir, E. N., Esposito, E., Gurgand, L., & Ramus, F. (2026) · Educational Psychology Review · doi:10.1007/s10648-026-10117-8 · Cited by 7 · see citing works
CEALLAIGH, T. Ó., & Murphy, S. (2026) · Computers and Education Open · doi:10.1016/j.caeo.2026.100367 · Cited by 10 · see citing works
Modelling the unique contributions of task understanding to academic challenges and performance
Olivares, L. M. B., Rostampour, R., & Hadwin, A. F. (2024) · Metacognition and Learning · doi:10.1007/s11409-024-09402-0 · Cited by 7 · see citing works
“Similarly, there may be value sampling these task-specific self-reports for multiple study episodes and coupling those with multi-modal traces of studying (Engelmann & Bannert, 2021; Greene, et al., 2021; Järvelä, et al., 2021; Lim, et al., 2021; Taub, et al., 2021).”
Tang, X., Jiang, L., Liu, G., & Li, H. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1610550 · Cited by 6 · see citing works
An Innovative Framework to Improve Course and Student Outcomes
Alalawi, K., Athauda, R., & Chiong, R. (2021) · International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) · doi:10.1109/citisia53721.2021.9719985 · Cited by 6 · see citing works
Wang, Z., Cao, Y., & Gong, S. (2022) · Journal of Educational Computing Research · doi:10.1177/07356331221132079 · Cited by 6 · see citing works
InPath Forum: A Real-Time Learning Analytics and Performance Ranking Forum System
Yi, A. C. Y., Ying, T. K., Yee, S. J., Wee, M. C., & Tin, T. T. (2022) · IEEE Access · doi:10.1109/access.2022.3227430 · Cited by 6 · see citing works
“[14], [15].”
Zhang, L., Wu, M., & Ouyang, F. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11940-0 · Cited by 6 · see citing works
“…students’ information and trace data, LA tools have been widely applied to help students make reflection, promote students to increase awareness of the learning process, and support instructors to provide learning guidance (Lim et al., 2019; Papamitsiou and Economides, 2015; Pardo et al., 2018).”
Powerful Student-Facing Dashboard Design Through Effective Feedback, Visualization, and Gamification
Bayrak, F., Kibar, P. N., & Kocadere, S. A. (2021) · Advances in analytics for learning and teaching · doi:10.1007/978-3-030-81222-5_7 · Cited by 6 · see citing works
Lim, L.-A., Atif, A., & Farmer, I. W. (2022) · ASCILITE Publications · doi:10.14742/apubs.2022.55 · Cited by 6 · see citing works
“Emerging research in learning analytics feedback interventions has shown benefits for students’ self-regulated learning (Lim et al., 2020) and performance (Lim et al., 2021) in blended learning settings.”
BackgroundMethodSelf-citationZhou, Q., Suraworachet, W., & Cukurova, M. (2021) · doi:10.35542/osf.io/u3g4n · Cited by 6 · see citing works
“Previous research has reinforced the usual higher predictive accuracy of models generated from multimodal compared to unimodal data [19-21] SRL research with MMLA has been introduced in many contexts such as individual distance learning [22-24] and collaborative learning [25-28].”
ResultInvestigating Student and Teacher Perceptions in e-Learning with Learning Analytics and Ontologies
Costa, L., da Silveira, A. C., Souza, M., Salvador, L. N., & Santos, C. A. S. (2023) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v18i08.32411 · Cited by 5 · see citing works
Human-centered Approaches to Data-informed Feedback
Tsai, Y., & Martínez‐Maldonado, R. (2022) · Solar eBooks · doi:10.18608/hla22.021 · Cited by 5 · see citing works
Fries, A., Pirotte, M., Vanhee, L., Bonnet, P., Quatresooz, P., Debruyne, C., Marée, R., & Defaweux, V. (2023) · Anatomical Sciences Education · doi:10.1002/ase.2346 · Cited by 5 · see citing works
“Learning analytics can produce and transmit information about students' progress as learners, enabling the teacher to regulate and improve existing pedagogical practices (Lim et al., 2021).”
BackgroundUsing Institutional Data to Drive Quality, Improvement, and Innovation
Dart, S., & Cunningham, S. (2023) · University development and administration · doi:10.1007/978-981-19-9438-8_29-1 · Cited by 5 · see citing works
Feedback Assisted by Technology: A Systematic Review of Empirical Research
Huang, W., Stephens, J. M., & Brown, G. (2025) · International Journal of Technology in Education · doi:10.46328/ijte.1061 · Cited by 7 · see citing works
A meta-analysis on the effect of learning analytics interventions on students’ academic performance
Kokoç, M., Bütüner, S. Ö., & Güler, M. (2025) · Journal of Research on Technology in Education · doi:10.1080/15391523.2025.2536571 · Cited by 4 · see citing works
The paradigm wars rage: the need for an integrated approach for the future of higher education
Dollinger, M. (2023) · Advancing Scholarship and Research in Higher Education · doi:10.59197/asrhe.v4i1.8117 · Cited by 3 · see citing works
Sun, Y., Xu, X., & Zhang, Y. (2023) · International Conference on Education Technology and Computer · doi:10.1145/3629296.3629307 · Cited by 4 · see citing works
Sauchelli, I. B., Heath, G., Richardson, A., Lewis, S., & Lim, L.-A. (2023) · Student Success · doi:10.5204/ssj.2825 · Cited by 4 · see citing works
“Lim et al. (2021) demonstrated positive changes in SRL when technology-mediated feedback was introduced into a large first-year course.”
BackgroundMethodResultInfluentialSelf-citationPayne, A. L., Compton, M., & Kennedy, S. (2023) · Postdigital science and education · doi:10.1007/978-3-031-31875-7_7 · Cited by 4 · see citing works
Heikkinen, S., Saqr, M., Malmberg, J., & Tedre, M. (2022) · Research Square · doi:10.21203/rs.3.rs-1738740/v1 · Cited by 4 · see citing works
- Authors
- Lim, L.-A., Gentili, S., Pardo, A., Kovanović, V., Whitelock-Wainwright, A., Gašević, D., & Dawson, S.
- Affiliations
- University of South Australia (AU)
- Monash University (AU)
- Corresponding author
- Lim, Lisa-Angelique
- ORCID
- Venue
- Learning and Instruction
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 72
- Pages
- 101202
- ISSN
- 0959-4752 (ISSN-L)
- OpenAlex
- W2945685654
- Cited by
- 159
- References
- 52
- Citations by year
- 2026: 16 · 2025: 20 · 2024: 26 · 2023: 32 · 2022: 27 · 2021: 18 · 2020: 14 · 2019: 6
- FWCI
- 17.64
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- Learning and Instruction (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- UniSA Research Outputs Repository (University of South Australia) (submittedVersion)
- HAL (submittedVersion)
- Funders
- Office for Learning and Teaching
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- learning analytics, process feedback, student self-regulation, academic performance, personalized feedback, prior academic achievement, e-book usage
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