Aronson, L., Niehaus, B., Hill-Sakurai, L., Lai, C., & O’Sullivan, P. S. (2012). A comparison of two methods of teaching reflective ability in Year 3 medical students: Comparison of teaching methods for reflection. Medical Education, 46(8), 807–814. https://doi.org/10.1111/j.1365-2923.2012.04299.x.
Article
Google Scholar
Bodily, R., Verbert, K. (2017). Trends and issues in student-facing learning analytics reporting systems research. In: Proceedings of the Seventh International Learning Analytics & Knowledge Conference. Vancouver British Columbia Canada: ACM, pp. 309–318. https://doi.org/10.1145/3027385.3027403
Boutet, I., Vandette, M. P., & Valiquette-Tessier, S.-C. (2017). Evaluating the implementation and effectiveness of reflection writing. The Canadian Journal for the Scholarship of Teaching and Learning. https://doi.org/10.5206/cjsotl-rcacea.2017.1.8.
Article
Google Scholar
Bridgeman, B., & Ramineni, C. (2017). Design and evaluation of automated writing evaluation models: Relationships with writing in naturalistic settings. Assessing Writing, 34, 62–71. https://doi.org/10.1016/j.asw.2017.10.001.
Article
Google Scholar
Carpenter, S.K. (2014). Spacing and interleaving of study and practice. In: Applying science of learning in education: Infusing psychological science into the curriculum. Washington, DC, US: Society for the Teaching of Psychology, pp. 131–141.
Connor-Greene, P. A. (2000). Making connections: evaluating the effectiveness of journal writing in enhancing student learning. Teaching of Psychology, 27(1), 44–46. https://doi.org/10.1207/S15328023TOP2701_10.
Article
Google Scholar
Cotos, E., Huffman, S., & Link, S. (2020). Understanding graduate writers’ interaction with and impact of the research writing tutor during revision. Journal of Writing Research, 12(1), 187–232. https://doi.org/10.17239/jowr-2020.12.01.07.
Article
Google Scholar
Crossley, S. A., Kim, M., Allen, L., & McNamara, D. (2019). Automated summarization evaluation (ASE) using natural language processing tools. In S. Isotani, E. Millán, A. Ogan, P. Hastings, B. McLaren, & R. Luckin (Eds.), Artificial Intelligence in Education (pp. 84–95). Springer International Publishing.
Chapter
Google Scholar
Cukurova, M. (2019). Learning analytics as AI extenders in education: Multimodal machine learning versus multimodal learning analytics. In: Artificial intelligence and adaptive education. Vol. 2019. AIAED.
Cukurova, M., Bennett, J., & Abrahams, I. (2018). Students’ knowledge acquisition and ability to apply knowledge into different science contexts in two different independent learning settings. Research in Science & Technological Education, 36(1), 17–34. https://doi.org/10.1080/02635143.2017.1336709.
Article
Google Scholar
Cukurova, M., Kent, C., & Luckin, R. (2019). Artificial intelligence and multimodal data in the service of human decision-making: A case study in debate tutoring. British Journal of Educational Technology, 50(6), 3032–3046.
Article
Google Scholar
Dekker, H., Schönrock-Adema, J., Snoek, J. W., van der Molen, T., & Cohen-Schotanus, J. (2013). Which characteristics of written feedback are perceived as stimulating students’ reflective competence: an exploratory study. BMC Medical Education, 13(1), 94. https://doi.org/10.1186/1472-6920-13-94.
Article
Google Scholar
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059.
Article
Google Scholar
Gibson, A., Aitken, A., Sándor, A., Shum, S.B., Tsingos-Lucas, C., Knight, S. (2017). Reflective writing analytics for actionable feedback. In: Proceedings of the Seventh International Learning Analytics & Knowledge Conference. Vancouver British Columbia Canada: ACM, pp. 153–162. https://doi.org/10.1145/3027385.3027436
Graham, S., & Harris, K. R. (1994). The role and development of self-regulation in the writing process. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulation of learning and performance: Issues and educational applications (Vol. 1, pp. 203–228). Lawrence Erlbaum Associates Inc.
Google Scholar
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487.
Article
Google Scholar
Hyndman, R.J., Athanasopoulos, G. (2018). Forecasting: Principles and practice. 2nd. OTexts. OTexts.com/fpp2.
Iraj, H., Fudge, A., Faulkner, M., Pardo, A., Kovanović, V. (2020). Understanding students’ engagement with personalised feedback messages”. In: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. Frankfurt Germany: ACM, pp. 438–447. https://doi.org/10.1145/3375462.3375527
Jivet, I., Wong, J., Scheffel, M., Torre, M.V., Specht, M., Drachsler, H. (2021). Quantum of Choice: How learners’ feedback monitoring decisions, goals and self-regulated learning skills are related. In: LAK21: 11th international learning analytics and knowledge conference. pp. 416–427.
Kovanović, V., Joksimović, S., Mirriahi, N., Blaine, E., Gašević, D., Siemens, G., Dawson, S. (2018). Understand students’ self-reflections through learning analytics. In: Proceedings of the 8th International Conference on Learning Analytics and Knowledge. Sydney New South Wales Australia: ACM, pp. 389–398. https://doi.org/10.1145/3170358.3170374
Liu, M., Kitto, K., & Shum, S. B. (2021). Combining factor analysis with writing analytics for the formative assessment of written reflection. Computers in Human Behavior, 120, 106733. https://doi.org/10.1016/j.chb.2021.106733.
Article
Google Scholar
Luckin, R. (2018). Machine Learning and Human Intelligence: The future of education for the 21st century. ERIC.
MacQueen, J. (1967). Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. 1: 281–197.
McIntosh, P. (2010). Action research and reflective practice: Creative and visual methods to facilitate reflection and learning. Routledge.
Book
Google Scholar
Mitchell, K. M., McMillan, D. E., & Rabbani, R. (2019). An exploration of writing self-efficacy and writing self-regulatory behaviours in undergraduate writing. The Canadian Journal for the Scholarship of Teaching and Learning. https://doi.org/10.5206/cjsotl-rcacea.2019.2.8175.
Article
Google Scholar
Nelson, K. J., Quinn, C., Marrington, A., & Clarke, J. A. (2012). Good practice for enhancing the engagement and success of commencing students. Higher Education, 63(1), 83–96. https://doi.org/10.1007/s10734-011-9426-y.
Article
Google Scholar
Neto, V., Rolim, V., Pinheiro, A., Lins, R. D., Gašević, D., & Mello, R. F. (2021). Automatic content analysis of online discussions for cognitive presence: A study of the generalizability across educational contexts. IEEE Transactions on Learning Technologies, 14(3), 299–312. https://doi.org/10.1109/TLT.2021.3083178.
Article
Google Scholar
Öncel, P., Flynn, L.E., Sonia, A.N., Barker, K.E., Lindsay, G.C., McClure, C.M., McNamara, D.S., Allen, L.K. (2021). Automatic student writing evaluation: investigating the impact of individual differences on source-based writing. In: LAK21: 11th International Learning Analytics and Knowledge Conference. ACM, pp. 620–625. https://doi.org/10.1145/3448139.3448207
Page, E. B. (1958). Teacher comments and student performance: A seventy-four classroom experiment in school motivation. Journal of Educational Psychology, 49(4), 173–181. https://doi.org/10.1037/h0041940.
Article
Google Scholar
Plak, S., van Klaveran, C., Cornelisz, I. (2022). Raising student engagement using digital nudges tailored to students’ motivation and perceived ability levels. British Journal of Educational Technology. in press.
Rohrer, D. (2012). Interleaving helps students distinguish among similar concepts. Educational Psychology Review, 24(3), 355–367.
Article
MathSciNet
Google Scholar
Rohrer, D., & Taylor, K. (2006). The effects of overlearning and distributed practise on the retention of mathematics knowledge. Applied Cognitive Psychology, 20(9), 1209–1224. https://doi.org/10.1002/acp.1266.
Article
Google Scholar
Rozental, L., Meitar, D., & Karnieli-Miller, O. (2021). Medical students’ experiences and needs from written reflective journal feedback. Medical Education, 55(4), 505–517. https://doi.org/10.1111/medu.14406.
Article
Google Scholar
Ryan, M. (2013). The pedagogical balancing act: Teaching reflection in higher education. Teaching in Higher Education, 18(2), 144–155. https://doi.org/10.1080/13562517.2012.694104.
Article
Google Scholar
Royce Sadler, D. (2010). Beyond feedback: Developing student capability in complex appraisal. Assessment & Evaluation in Higher Education, 35(5), 535–550. https://doi.org/10.1080/02602930903541015.
Article
Google Scholar
Shibani, A. (2020). Constructing automated revision graphs: A novel visualization technique to study student writing. In I. I. Bittencourt, M. Cukurova, K. Muldner, R. Luckin, & E. Millán (Eds.), Artificial Intelligence in Education (pp. 285–290). Springer International Publishing.
Chapter
Google Scholar
Shibani, A., Knight, S., Shum, S. B. (2019). Contextualizable learning analytics design: A generic model and writing analytics evaluations. In: Proceedings of the 9th International Conference on Learning Analytics & Knowledge. ACM, pp. 210–219. https://doi.org/10.1145/3303772.3303785
Shin, Y. (2017). Time series analysis in the social sciences: The fundamentals. University of California Press. https://doi.org/10.1525/9780520966383.
Book
Google Scholar
Shum, S. B., Knight, S., McNamara, D., Allen, L., Bektik, D., Crossley, S. (2016). Critical perspectives on writing analytics. In: LAK16: 6th International Learning Analytics and Knowledge Conference. ACM Press, pp. 481–483. https://doi.org/10.1145/2883851.2883854
Sitzmann, T., & Ely, K. (2011). A meta-analysis of self-regulated learning in work-related training and educational attainment: What we know and where we need to go. Psychological Bulletin, 137(3), 421–442. https://doi.org/10.1037/a0022777.
Article
Google Scholar
Sobel, H. S., Cepeda, N. J., & Kapler, I. V. (2011). Spacing effects in real-world classroom vocabulary learning. Applied Cognitive Psychology, 25(5), 763–767. https://doi.org/10.1002/acp.1747.
Article
Google Scholar
Stewart, L. G., & White, M. A. (1976). Teacher comments, letter grades, and student performance: What do we really know? Journal of Educational Psychology, 68(4), 488–500. https://doi.org/10.1037/0022-0663.68.4.488.
Article
Google Scholar
Strong, R. W., Silver, H. F., & Perini, M. J. (2001). Making students as important as standards. ASCD Educational Leadership, 59(3), 56–61.
Google Scholar
Suraworachet, W., Villa-Torrano, C., Zhou, Q., Asensio-Pérez, J. I., Dimitriadis, Y., & Cukurova, M. (2021). Examining the relationship between reflective writing behaviour and self-regulated Learning competence: A time-series analysis. In T. De Laet, R. Klemke, C. Alario-Hoyos, I. Hilliger, & A. Ortega-Arranz (Eds.), Technology-Enhanced Learning for a Free, Safe, and Sustainable World (Vol. 12884, pp. 163–177). Springer International Publishing. https://doi.org/10.1007/978-3-030-86436-1_13.
Chapter
Google Scholar
Thorpe, K. (2004). Reflective learning journals: From concept to practice. Reflective Practice, 5(3), 327–343. https://doi.org/10.1080/1462394042000270655.
Article
Google Scholar
Türkay, S., Seaton, D., Ang, A. M. (2018). Itero: A revision history analytics tool for exploring writing behavior and reflection. In: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, pp. 1–6. https://doi.org/10.1145/3170427.3188474.
Vytasek, J. M., Patzak, A., & Winne, P. H. (2020). Analytics for student engagement. In M. Virvou, E. Alepis, G. A. Tsihrintzis, & L. C. Jain (Eds.), Machine Learning Paradigms Advances in Learning Analytics (pp. 23–48). Springer International Publishing. https://doi.org/10.1007/978-3-030-13743-4_3.
Chapter
Google Scholar
Wingate, U. (2010). The impact of formative feedback on the development of academic writing. Assessment & Evaluation in Higher Education, 35(5), 519–533. https://doi.org/10.1080/02602930903512909.
Article
Google Scholar
Winograd, B. A., Dood, A. J., Moeller, R., Moon, A., Gere, A., Shultz, G. (2021). Detecting high orders of cognitive complexity in students’ reasoning in argumentative writing about ocean acidification. In: LAK21: 11th International Learning Analytics and Knowledge Conference. ACM, pp. 586–591. https://doi.org/10.1145/3448139.3448202.
Yip, M. C. W. (2012). Learning strategies and self-efficacy as predictors of academic performance: A preliminary study. Quality in Higher Education, 18(1), 23–34. https://doi.org/10.1080/13538322.2012.667263.
Article
MathSciNet
Google Scholar
Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81, 329–339. https://doi.org/10.1037/0022-0663.81.3.329.
Article
Google Scholar
Zimmerman, Barry J., & Risemberg, Rafael. (1997). Becoming a self-regulated writer: A social cognitive perspective. Contemporary Educational Psychology, 22(1), 73–101. https://doi.org/10.1006/ceps.1997.0919.
Article
Google Scholar