The Relationship between Wellbeing and Academic Achievement: A Comprehensive Cross-Sectional Analysis of System Wide Data From 2016-2019
DOI:
https://doi.org/10.18608/jla.2024.8357Keywords:
student wellbeing, academic achievement, wellbeing engagement collection, research paperAbstract
Learning analytics research has long flagged the importance of social and emotional well-being on student academic progress and outcomes. However, few studies have examined the interplay between well-being measures and academic outcomes at scale. This research examined the relationship between the Well-being Engagement Collection (WEC) index and student academic outcomes, using cross-sectional panel data from 215,635 students in Years 4–10 in South Australia, spanning 2016 to 2019. Using linear hierarchical mixed models, results indicate a modest impact of the WEC index on these outcomes, with learning readiness emerging as the most influential component. The effects of the WEC index remained stable across various student year levels and census periods. A notable finding was the more pronounced influence of the WEC index on male students, particularly in literacy, suggesting gender-specific variations in the role of emotional well-being on academic achievement. The study underscores the potential of learning analytics in future investigations to deepen our understanding of the nexus between socio-emotional factors and academic outcomes.
References
Adler, A. (2017). Well-being and academic achievement: Towards a new evidence-based educational paradigm. In M. A. White, G. R. Slemp, & A. S. Murray (Eds.), Future directions in well-being: Education, organizations and policy (pp. 203–208). Springer International Publishing. https://doi.org/10.1007/978-3-319-56889-8_35
Ahmadi, S., Hassani, M., & Ahmadi, F. (2020). Student- and school-level factors related to school belongingness among high school students. International Journal of Adolescence and Youth, 25(1), 741–752. https://doi.org/10.1080/02673843.2020.1730200
Amholt, T. T., Dammeyer, J., Carter, R., & Niclasen, J. (2020). Psychological well-being and academic achievement among school-aged children: A systematic review. Child Indicators Research, 13(4), 1523–1548. https://doi.org/10.1007/s12187-020-09725-9
Antaramian, S. (2017). The importance of very high life satisfaction for students’ academic success. Cogent Education, 4(1), 1307622. https://doi.org/10.1080/2331186X.2017.1307622
Arnold, K. E., & Pistilli, M. D. (2012). Course signals at Purdue: Using learning analytics to increase student success. In S. Buckingham Shum, D. Gašević, & R. Ferguson (Eds.), Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK ʼ12), 29 April–2 May 2012, Vancouver, BC, Canada (pp. 267–270). ACM Press. https://doi.org/10.1145/2330601.2330666
Au, W. (2022). Unequal by design: High-stakes testing and the standardization of inequality (2nd ed.). Routledge.
Australian Bureau of Statistics. (2011). Socio-economic indexes for areas (SEIFA). Australian Bureau of Statistics.
Azevedo, R., Millar, G. C., Taub, M., Mudrick, N. V., Bradbury, A. E., & Price, M. J. (2017). Using data visualizations to foster emotion regulation during self-regulated learning with advanced learning technologies: A conceptual framework. Proceedings of the 7th International Learning Analytics and Knowledge Conference (LAK ’17), 13–17 March 2017, Vancouver, BC, Canada (pp. 444–448). ACM Press. https://doi.org/10.1145/3027385.3027440
Bang, H., Won, D., & Park, S. (2020). School engagement, self-esteem, and depression of adolescents: The role of sport participation and volunteering activity and gender differences. Children and Youth Services Review, 113, 105012. https://doi.org/10.1016/j.childyouth.2020.105012
Barthakur, A., Dawson, S., & Kovanovic, V. (2023). Advancing leaner profiles with learning analytics: A scoping review of current trends and challenges. Proceedings of the 13th International Conference on Learning Analytics and Knowledge (LAK ’23), 13–17 March 2017, Arlington, TX, USA (pp. 606–612). ACM Press. https://doi.org/10.1145/3576050.3576083
Boulton, C. A., Hughes, E., Kent, C., Smith, J. R., & Williams, H. T. P. (2019). Student engagement and wellbeing over time at a higher education institution. PloS One, 14(11), e0225770. https://doi.org/10.1371/journal.pone.0225770
Bücker, S., Nuraydin, S., Simonsmeier, B. A., Schneider, M., & Luhmann, M. (2018). Subjective well-being and academic achievement: A meta-analysis. Journal of Research in Personality, 74, 83–94. https://doi.org/10.1016/j.jrp.2018.02.007
Burleson, W. (2013). Affective learning companions and the adoption of metacognitive strategies. In R. Azevedo & V. Aleven (Eds.), International handbook of metacognition and learning technologies (pp. 645–657). Springer. https://doi.org/10.1007/978-1-4419-5546-3_42
Cadime, I., Pinto, A. M., Lima, S., Rego, S., Pereira, J., & Ribeiro, I. (2016). Well‐being and academic achievement in secondary school pupils: The unique effects of burnout and engagement. Journal of Adolescence, 53(1), 169–179. https://doi.org/10.1016/j.adolescence.2016.10.003
Conijn, R., Snijders, C., Kleingeld, A., & Matzat, U. (2016). Predicting student performance from LMS data: A comparison of 17 blended courses using Moodle LMS. IEEE Transactions on Learning Technologies, 10(1), 17–29. https://doi.org/10.1109/TLT.2016.2616312
Credé, M., Tynan, M. C., & Harms, P. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology, 113(3), 492–511. https://doi.org/10.1037/pspp0000102
Csikszentmihalyi, M. (1999). If we are so rich, why aren’t we happy? American Psychologist, 54(10), 821–827.
Darling-Hammond, L., Flook, L., Cook-Harvey, C., Barron, B., & Osher, D. (2020). Implications for educational practice of the science of learning and development. Applied Developmental Science, 24(2), 97–140. https://doi.org/10.1080/10888691.2018.1537791
Davis, S. K., & Hadwin, A. F. (2021). Exploring differences in psychological well-being and self-regulated learning in university student success. Frontline Learning Research, 9(1), 30–43. https://doi.org/10.14786/flr.v9i1.581
Dawson, S., Poquet, O., Colvin, C., Rogers, T., Pardo, A., & Gasevic, D. (2018). Rethinking learning analytics adoption through complexity leadership theory. Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK ’18), 5–9 March 2018, Sydney, NSW, Australia (pp. 236–244). ACM Press. https://doi.org/10.1145/3170358.3170375
de Lijster, J. M., Dieleman, G. C., Utens, E. M. W. J., Dierckx, B., Wierenga, M., Verhulst, F. C., & Legerstee, J. S. (2018). Social and academic functioning in adolescents with anxiety disorders: A systematic review. Journal of Affective Disorders, 230, 108–117. https://doi.org/10.1016/j.jad.2018.01.008
Deng, Y., Chang, L., Yang, M., Huo, M., & Zhou, R. (2016). Gender differences in emotional response: Inconsistency between experience and expressivity. PloS One, 11(6), e0158666. https://doi.org/10.1371/journal.pone.0158666
Di Pietro, G. (2023). The impact of COVID-19 on student achievement: Evidence from a recent meta-analysis. Educational Research Review, 39, 100530. https://doi.org/10.1016/j.edurev.2023.100530
DiPerna, J. C., Volpe, R. J., & Elliott, S. N. (2005). A model of academic enablers and mathematics achievement in the elementary grades. Journal of School Psychology, 43(5), 379–392. https://doi.org/10.1016/j.jsp.2005.09.002
Diseth, Å., & Samdal, O. (2014). Autonomy support and achievement goals as predictors of perceived school performance and life satisfaction in the transition between lower and upper secondary school. Social Psychology of Education, 17(2), 269–291. https://doi.org/10.1007/s11218-013-9244-4
Eriksson, K., Björnstjerna, M., & Vartanova, I. (2020). The relation between gender egalitarian values and gender differences in academic achievement. Frontiers in Psychology, 11, 236. https://doi.org/10.3389/fpsyg.2020.00236
Esteban-Gonzalo, S., Esteban-Gonzalo, L., Cabanas-Sánchez, V., Miret, M., & Veiga, O. L. (2020). The investigation of gender differences in subjective well-being in children and adolescents: The UP&DOWN study. International Journal of Environmental Research and Public Health, 17(8), 2732. https://doi.org/10.3390/ijerph17082732
Fives, A., Russell, D., Kearns, N., Lyons, R., Eaton, P., Canavan, J., Devaney, C., & O’Brien, A. (2014). The association between academic self‐beliefs and reading achievement among children at risk of reading failure. Journal of Research in Reading, 37(2), 215–232. https://doi.org/10.1111/1467-9817.12025
Frome, P. M., & Eccles, J. S. (1998). Parents’ influence on children’s achievement-related perceptions. Journal of Personality and Social Psychology, 74(2), 435–452. https://doi.org/10.1037/0022-3514.74.2.435
Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (2016). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success. The Internet and Higher Education, 28, 68–84. https://doi.org/10.1016/j.iheduc.2015.10.002
Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64–71. https://doi.org/10.1007/s11528-014-0822-x
Girelli, L. (2023). What does gender has to do with math? Complex questions require complex answers. Journal of Neuroscience Research, 101(5), 679–688. https://doi.org/10.1002/jnr.25056
Gómez-Molinero, R., Zayas, A., Ruíz-González, P., & Guil, R. (2018). Optimism and resilience among university students. International Journal of Developmental and Educational Psychology, 1(1), 147–154. https://doi.org/10.17060/ijodaep.2018.n1.v1.1179
Gregory, T., & Brinkman, S. (2020). Wellbeing and engagement collection (WEC): History of the WEC in the South Australian school system and psychometric properties of the WEC survey instrument. https://www.education.sa.gov.au/docs/system-performance/fraser-mustard-centre/sa-wec-technical-report.pdf
Gregory, T., Engelhardt, D., Lewkowicz, A., Luddy, S., Guhn, M., Gadermann, A., Schonert-Reichl, K., & Brinkman, S. (2019). Validity of the middle years development instrument for population monitoring of student wellbeing in Australian school children. Child Indicators Research, 12(3), 873–899. https://doi.org/10.1007/s12187-018-9562-3
Gregory, T., Sincovich, A., Brushe, M., Finlay-Jones, A., Collier, L. R., Grace, B., Monroy, N. S., & Brinkman, S. A. (2021). Basic epidemiology of wellbeing among children and adolescents: A cross-sectional population level study. SSM – Population Health, 15, 100907. https://doi.org/10.1016/j.ssmph.2021.100907
Hakimzadeh, R., Besharat, M.-A., Khaleghinezhad, S. A., & Ghorban Jahromi, R. (2016). Peers’ perceived support, student engagement in academic activities and life satisfaction: A structural equation modeling approach. School Psychology International, 37(3), 240–254. https://doi.org/10.1177/0143034316630020
Harris, A., & Goodall, J. (2008). Do parents know they matter? Engaging all parents in learning. Educational Research, 50(3), 277–289. https://doi.org/10.1080/00131880802309424
Hoofman, J., & Secord, E. (2021). The effect of COVID-19 on education. Pediatric Clinics of North America, 68(5), 1071–1079. https://doi.org/10.1016/j.pcl.2021.05.009
Huang, C. (2013). Gender differences in academic self-efficacy: A meta-analysis. European Journal of Psychology of Education, 28(1), 1–35. https://doi.org/10.1007/s10212-011-0097-y
Hughes, C. (2020). Some implications of COVID-19 for remote learning and the future of schooling. UNESCO. https://coilink.org/20.500.12592/smwr7z
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Jiao, W. Y., Wang, L. N., Liu, J., Fang, S. F., Jiao, F. Y., Pettoello-Mantovani, M., & Somekh, E. (2020). Behavioral and emotional disorders in children during the COVID-19 epidemic. The Journal of Pediatrics, 221, 264–266. https://doi.org/10.1016/j.jpeds.2020.03.013
Joksimović, S., Siemens, G., Wang, Y. E., San Pedro, M. O. Z., & Way, J. (2020). Editorial: Beyond cognitive ability. Journal of Learning Analytics, 7(1), 1–4. https://doi.org/10.18608/jla.2020.71.1
Juvonen, J., Espinoza, G., & Knifsend, C. (2012). The role of peer relationships in student academic and extracurricular engagement. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 387–401). Springer. https://doi.org/10.1007/978-1-4614-2018-7_18
Kenward, M. G., & Roger, J. H. (1997). Small sample inference for fixed effects from restricted maximum likelihood. Biometrics, 53(3), 983–997. https://doi.org/10.2307/2533558
Kern, M. L., Benson, L., Steinberg, E. A., & Steinberg, L. (2016). The EPOCH measure of adolescent well-being. Psychological Assessment, 28(5), 586–597. https://doi.org/10.1037/pas0000201
Kern, M. L., Waters, L. E., Adler, A., & White, M. A. (2015). A multidimensional approach to measuring well-being in students: Application of the PERMA framework. The Journal of Positive Psychology, 10(3), 262–271. https://doi.org/10.1080/17439760.2014.936962
Khalaila, R. (2015). The relationship between academic self-concept, intrinsic motivation, test anxiety, and academic achievement among nursing students: Mediating and moderating effects. Nurse Education Today, 35(3), 432–438. https://doi.org/10.1016/j.nedt.2014.11.001
Khesht-Masjedi, M. F., Shokrgozar, S., Abdollahi, E., Habibi, B., Asghari, T., Ofoghi, R. S., & Pazhooman, S. (2019). The relationship between gender, age, anxiety, depression, and academic achievement among teenagers. Journal of Family Medicine and Primary Care, 8(3), 799–804. https://doi.org/10.4103/jfmpc.jfmpc_103_18
Korpershoek, H., Canrinus, E. T., Fokkens-Bruinsma, M., & de Boer, H. (2020). The relationships between school belonging and students’ motivational, social-emotional, behavioural, and academic outcomes in secondary education: A meta-analytic review. Research Papers in Education, 35(6), 641–680. https://doi.org/10.1080/02671522.2019.1615116
Korucu, I., Ayturk, E., Finders, J. K., Schnur, G., Bailey, C. S., Tominey, S. L., & Schmitt, S. A. (2022). Self-regulation in preschool: Examining its factor structure and associations with pre-academic skills and social-emotional competence. Frontiers in Psychology, 12, 717317. https://doi.org/10.3389/fpsyg.2021.717317
Kraft, M. A., & Dougherty, S. M. (2013). The effect of teacher–family communication on student engagement: Evidence from a randomized field experiment. Journal of Research on Educational Effectiveness, 6(3), 199–222. https://doi.org/10.1080/19345747.2012.743636
Lam, B., Brinkman, S., Engelhardt, D., Gotts, R., & Oakley, A. (2023). Leveraging data to support young people’s education and wellbeing dataset (Version 0.1) [Data set]. Fraser Mustard Centre. https://doi.org/10.5281/ZENODO.10199486
Lazarides, R., & Raufelder, D. (2021). Control‐value theory in the context of teaching: Does teaching quality moderate relations between academic self‐concept and achievement emotions? British Journal of Educational Psychology, 91(1), 127–147. https://doi.org/10.1111/bjep.12352
Liu, J., Bullock, A., Coplan, R. J., Chen, X., Li, D., & Zhou, Y. (2018). Developmental cascade models linking peer victimization, depression, and academic achievement in Chinese children. British Journal of Developmental Psychology, 36(1), 47–63. https://doi.org/10.1111/bjdp.12212
Liu, X., He, W., Zhao, L., & Hong, J.-C. (2021). Gender differences in self-regulated online learning during the COVID-19 lockdown. Frontiers in Psychology, 12, 752131. https://doi.org/10.3389/fpsyg.2021.752131
Logan, S., & Johnston, R. (2009). Gender differences in reading ability and attitudes: Examining where these differences lie. Journal of Research in Reading, 32(2), 199–214. https://doi.org/10.1111/j.1467-9817.2008.01389.x
Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 31–40. https://er.educause.edu/articles/2011/9/penetrating-the-fog-analytics-in-learning-and-education
Lyons, M. D., & Huebner, E. S. (2016). Academic characteristics of early adolescents with higher levels of life satisfaction. Applied Research in Quality of Life, 11(3), 757–771. https://doi.org/10.1007/s11482-015-9394-y
Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588–599. https://doi.org/10.1016/j.compedu.2009.09.008
Mahdiuon, R., Salimi, G., & Raeisy, L. (2020). Effect of social media on academic engagement and performance: Perspective of graduate students. Education and Information Technologies, 25(4), 2427–2446. https://doi.org/10.1007/s10639-019-10032-2
Marsh, H. W., & Martin, A. J. (2011). Academic self‐concept and academic achievement: Relations and causal ordering. British Journal of Educational Psychology, 81(1), 59–77. https://doi.org/10.1348/000709910X503501
Marzouk, Z., Rakovic, M., Liaqat, A., Vytasek, J., Samadi, D., Stewart-Alonso, J., Ram, I., Woloshen, S., Winne, P. H., & Nesbit, J. C. (2016). What if learning analytics were based on learning science? Australasian Journal of Educational Technology, 32(6). https://doi.org/10.14742/ajet.3058
McClelland, M. M., Cameron, C. E., Duncan, R., Bowles, R. P., Acock, A. C., Miao, A., & Pratt, M. E. (2014). Predictors of early growth in academic achievement: The head-toes-knees-shoulders task. Frontiers in Psychology, 5, 599. https://doi.org/10.3389/fpsyg.2014.00599
McGaw, B., Louden, W., & Wyatt-Smith, C. (2020). NAPLAN review final report. Department of Education and Training (NSW).
McGeown, S., Goodwin, H., Henderson, N., & Wright, P. (2012). Gender differences in reading motivation: Does sex or gender identity provide a better account? Journal of Research in Reading, 35(3), 328–336. https://doi.org/10.1111/j.1467-9817.2010.01481.x
Mega, C., Ronconi, L., & De Beni, R. (2014). What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. Journal of Educational Psychology, 106(1), 121–131. https://doi.org/10.1037/a0033546
Mejía-Rodríguez, A. M., Luyten, H., & Meelissen, M. R. M. (2021). Gender differences in mathematics self-concept across the world: An exploration of student and parent data of TIMSS 2015. International Journal of Science and Mathematics Education, 19(6), 1229–1250. https://doi.org/10.1007/s10763-020-10100-x
Mendez, I. (2015). The effect of the intergenerational transmission of noncognitive skills on student performance. Economics of Education Review, 46, 78–97. https://doi.org/10.1016/j.econedurev.2015.03.001
Miller, S., Connolly, P., & Maguire, L. K. (2013). Wellbeing, academic buoyancy and educational achievement in primary school students. International Journal of Educational Research, 62, 239–248. https://doi.org/10.1016/j.ijer.2013.05.004
Milligan, S. (2020). Standards for developing assessments of learning using process data. In M. Bearman, P. Dawson, R. Ajjawi, J. Tai, & D. Boud (Eds.), Re-imagining university assessment in a digital world (pp. 179–192). Springer Cham. https://doi.org/10.1007/978-3-030-41956-1_13
Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., Houts, R., Poulton, R., Roberts, B. W., Ross, S., Sears, M. R., Thomson, W. M., & Caspi, A. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences, 108(7), 2693–2698. https://doi.org/10.1073/pnas.1010076108
Morinaj, J., & Hascher, T. (2022). On the relationship between student well-being and academic achievement. Zeitschrift Für Psychologie, 230(3). https://doi.org/10.1027/2151-2604/a000499
Moses, J. O., & Villodas, M. T. (2017). The potential protective role of peer relationships on school engagement in at-risk adolescents. Journal of Youth and Adolescence, 46(11), 2255–2272. https://doi.org/10.1007/s10964-017-0644-1
Nakamura, J., & Csikszentmihalyi, M. (2009). Flow theory and research. In S. J. Lopez & C. R. Snyder (Eds.), The Oxford handbook of positive psychology (2nd ed., pp. 195–206). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780195187243.013.0018
Ohtani, K., & Hisasaka, T. (2018). Beyond intelligence: A meta-analytic review of the relationship among metacognition, intelligence, and academic performance. Metacognition and Learning, 13, 179–212. https://doi.org/10.1007/s11409-018-9183-8
Pandey, A., Hale, D., Das, S., Goddings, A. L., Blakemore, S. J., & Viner, R. M. (2018). Effectiveness of universal self-regulation–based interventions in children and adolescents: A systematic review and meta-analysis. JAMA Pediatrics, 172(6), 566–575. https://doi.org/10.1001/jamapediatrics.2018.0232
Pardo, A., Ellis, R. A., & Calvo, R. A. (2015). Combining observational and experiential data to inform the redesign of learning activities. Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK ’15), 16–20 March 2015, Poughkeepsie, NY, USA (pp. 305–309). ACM Press. https://doi.org/10.1145/2723576.2723625
Parker, P. D., Marsh, H. W., Ciarrochi, J., Marshall, S., & Abduljabbar, A. S. (2014). Juxtaposing math self-efficacy and self-concept as predictors of long-term achievement outcomes. Educational Psychology, 34(1), 29–48. https://doi.org/10.1080/01443410.2013.797339
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315–341. https://doi.org/10.1007/s10648-006-9029-9
Quin, D., Heerde, J. A., & Toumbourou, J. W. (2018). Teacher support within an ecological model of adolescent development: Predictors of school engagement. Journal of School Psychology, 69, 1–15. https://doi.org/10.1016/j.jsp.2018.04.003
Renshaw, T. L., Long, A. C. J., & Cook, C. R. (2015). Assessing adolescents’ positive psychological functioning at school: Development and validation of the Student Subjective Wellbeing Questionnaire. School Psychology Quarterly, 30(4), 534–552. https://doi.org/10.1037/spq0000088
Retelsdorf, J., Schwartz, K., & Asbrock, F. (2015). “Michael can’t read!” Teachers’ gender stereotypes and boys’ reading self-concept. Journal of Educational Psychology, 107(1), 186–194. https://doi.org/10.1037/a0037107
Rodríguez, S., González-Suárez, R., Vieites, T., Piñeiro, I., & Díaz-Freire, F. M. (2022). Self-regulation and students well-being: A systematic review 2010–2020. Sustainability, 14(4), 2346. https://doi.org/10.3390/su14042346
Schumacher, C., & Ifenthaler, D. (2018). The importance of students’ motivational dispositions for designing learning analytics. Journal of Computing in Higher Education, 30(3), 599–619. https://doi.org/10.1007/s12528-018-9188-y
Schunk, D. H., & Zimmerman, B. J. (Eds.). (2008). Motivation and self-regulated learning: Theory, research, and applications. Lawrence Erlbaum Associates. https://doi.org/10.4324/9780203831076
Seligman, M. E. P., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. American Psychologist, 55(1), 5–14. https://doi.org/10.1037/0003-066X.55.1.5
Sellar, S. (2015). Data infrastructure: A review of expanding accountability systems and large-scale assessments in education. Discourse: Studies in the Cultural Politics of Education, 36(5), 765–777. https://doi.org/10.1080/01596306.2014.931117
Sghir, N., Adadi, A., & Lahmer, M. (2023). Recent advances in predictive learning analytics: A decade systematic review (2012–2022). Education and Information Technologies, 28(7), 8299–8333. https://doi.org/10.1007/s10639-022-11536-0
Sharif, H., & Atif, A. (2024). The evolving classroom: How learning analytics is shaping the future of education and feedback mechanisms. Education Sciences, 14(2), 176. https://doi.org/10.3390/educsci14020176
Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18(2), 158–176. https://doi.org/10.1521/scpq.18.2.158.21860
Star, J. R. (2015). When not to persevere: Nuances related to perseverance in mathematical problem solving. Harvard Graduate School of Education. https://web.archive.org/web/20150912151102/http://www.spencer.org/sites/default/files/pdfs/star_mip_0415.pdf
Tarabini, A., Curran, M., Montes, A., & Parcerisa, L. (2019). Can educational engagement prevent early school leaving? Unpacking the school’s effect on educational success. Educational Studies, 45(2), 226–241. https://doi.org/10.1080/03055698.2018.1446327
Thomas, D. P., Swain, N., Walton, J., & Hicks, D. (2023). Patterns in literacy gender gaps: Examining longitudinal data on boys’ achievements in the Australian NAPLAN test. International Journal of Educational Research, 120, 102207. https://doi.org/10.1016/j.ijer.2023.102207
Tomaszewski, W., Xiang, N., & Western, M. (2020). Student engagement as a mediator of the effects of socio‐economic status on academic performance among secondary school students in Australia. British Educational Research Journal, 46(3), 610–630. https://doi.org/10.1002/berj.3599
Tsai, Y.-S., Perrotta, C., & Gašević, D. (2020). Empowering learners with personalised learning approaches? Agency, equity and transparency in the context of learning analytics. Assessment & Evaluation in Higher Education, 45(4), 554–567. https://doi.org/10.1080/02602938.2019.1676396
Upadyaya, K., & Salmela-Aro, K. (2013). Development of school engagement in association with academic success and well-being in varying social contexts. European Psychologist, 18(2). https://doi.org/10.1027/1016-9040/a000143
van Rooij, E. C. M., Jansen, E. P. W. A., & van de Grift, W. J. C. M. (2017). Secondary school students’ engagement profiles and their relationship with academic adjustment and achievement in university. Learning and Individual Differences, 54, 9–19. https://doi.org/10.1016/j.lindif.2017.01.004
Vantieghem, W., & Van Houtte, M. (2015). Are girls more resilient to gender-conformity pressure? The association between gender-conformity pressure and academic self-efficacy. Sex Roles, 73(1–2), 1–15. https://doi.org/10.1007/s11199-015-0509-6
Viberg, O., Khalil, M., & Baars, M. (2020). Self-regulated learning and learning analytics in online learning environments: A review of empirical research. Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20), 23–27 March 2020, Frankfurt, Germany (pp. 524–533). ACM Press. https://doi.org/10.1145/3375462.3375483
Vilaplana-Pérez, A., Pérez-Vigil, A., Sidorchuk, A., Brander, G., Isomura, K., Hesselmark, E., Kuja-Halkola, R., Larsson, H., Mataix-Cols, D., & de la Cruz, L. F. (2021). Much more than just shyness: The impact of social anxiety disorder on educational performance across the lifespan. Psychological Medicine, 51(5), 861–869. https://doi.org/10.1017/S0033291719003908
Wentzel, K. R. (2022). Does anybody care? Conceptualization and measurement within the contexts of teacher–student and peer relationships. Educational Psychology Review, 34(4), 1919–1954. https://doi.org/10.1007/s10648-022-09702-4
Williams, K. H., Childers, C., & Kemp, E. (2013). Stimulating and enhancing student learning through positive emotions. Journal of Teaching in Travel & Tourism, 13(3), 209–227. https://doi.org/10.1080/15313220.2013.813320
Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Lawrence Erlbaum Associates.
Woolley, M. E., & Bowen, G. L. (2007). In the context of risk: Supportive adults and the school engagement of middle school students. Family Relations, 56(1), 92–104. https://doi.org/10.1111/j.1741-3729.2007.00442.x
Woolley, M. E., & Grogan‐Kaylor, A. (2006). Protective family factors in the context of neighborhood: Promoting positive school outcomes. Family Relations, 55(1), 93–104. https://doi.org/10.1111/j.1741-3729.2006.00359.x
Wu, H., Guo, Y., Yang, Y., Zhao, L., & Guo, C. (2021). A meta-analysis of the longitudinal relationship between academic self-concept and academic achievement. Educational Psychology Review, 33(4), 1749–1778. https://doi.org/10.1007/s10648-021-09600-1
Yang, C., Sharkey, J. D., Reed, L. A., Chen, C., & Dowdy, E. (2018). Bullying victimization and student engagement in elementary, middle, and high schools: Moderating role of school climate. School Psychology Quarterly, 33(1), 54–64. https://doi.org/10.1037/spq0000250
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Learning Analytics
This work is licensed under a Creative Commons Attribution 4.0 International License.
