Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition) ›› 2024, Vol. 60 ›› Issue (1): 92-103.doi: 10.16088/j.issn.1001-6597.2024.01.008

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Visual Learning Analysis for Promoting Teaching and Learning in a Smart Education Environment

WU Bian, CHEN Si-si   

  1. Department of Education Information Technology, East China Normal University, Shanghai 200062, China
  • Received:2023-01-15 Online:2024-01-25 Published:2024-02-26

Abstract: Big data has promoted the development of smart education and brought unprecedented challenges to the transformation and development of teaching—Overloaded data on education brings about difficulties for teachers to comprehend and solve diverse educational problems based on their individual experience, and subjective teaching strategies greatly affect teaching effectiveness. From the constructed theoretical framework of visual learning analysis, it is found that visual learning analysis can be applied to diverse typical educational scenarios and models, including online self-directed learning, offline curriculum learning, blended learning, the traditional teacher-centered classrooms, and student-centered constructivist classrooms. The application effectiveness of visual learning analysis should be evaluated from different indicator dimensions, such as visual attractiveness, usability, understanding level, frequency of use, satisfaction with use, perceived usefulness, learning effectiveness, and behavioral change. Future research needs to focus on how to improve the relevant abilities and literacy of teachers and students in applying visual learning analysis, and more scientifically verify the actual effectiveness of visual learning analysis tools.

Key words: smart education, data intelligence, visual learning analysis, learning analytical instruments

CLC Number:  G434
[1] Prinsloo P , Archer E , Barnes G, et al. Big(ger) data as better data in open distance learning: some provocations and theses[J]. International Review of Research in Open & Distributed Learning, 2015(1): 284-306.
[2] 祝智庭,贺斌.智慧教育:教育信息化的新境界[J].电化教育研究,2012(12):5-13.
[3] Ackoff R L. From data to wisdom[J].Journal of Applied Systems Analysis,1989(1):3-9.
[4] Song Y, Zhu Y. Big data and data science: what should we teach?[J]. Expert Systems,2016 (4) :364-373.
[5] Hrabowski F A, Suess J ,Fritz J. Assessment and analytics in institutional transformation[J]. Educause Review, 2011,46: 5 .
[6] Gelderblom G. Data-based decision making for instructional improvement in primary education[J]. International Journal of Educational Research, 2016, 80: 1-14.
[7] Khosravi H. Intelligent learning analytics dashboards: automated drill-down recommendations to support teacher data exploration[J]. Journal of Learning Analytics, 2021(3):133-154.
[8] Dervin B. Sense-making theory and practice: an overview of user interests in knowledge seeking and use[J]. Journal of Knowledge Management, 1998(2):36-46.
[9] Alhadad S S J. Visualizing data to support judgement, inference, and decision making in learning analytics: Insights from cognitive psychology and visualization science[J]. Journal of Learning Analytics, 2018(2):60-85.
[10] Keim D A, Mansmann F,Schneidewind J,et al. Visual analytics: scope and challenges [J].Visual Data Mining, 2008( 4404):76-90.
[11] 郑娅峰,赵亚宁,白雪,等.教育大数据可视化研究综述[J].计算机科学与探索,2021(3):403-422.
[12] Emmons S R, Light R P, Borner K. MOOC visual analytics: empowering students, teachers, researchers, and platform developers of massively open online courses [J] . Journal of the Association for Information Science and Technology ,2017(10): 2350-2363.
[13] Vieira C, Parsons P,Byrd V. Visual learning analytics of educational data: a systematic literature review and research agenda[J]. Computers & Education, 2018, 122 : 119-135.
[14] 胡立如,陈高伟.可视化学习分析:审视可视化技术的作用和价值[J].开放教育研究,2020(2):63-74.
[15] 张振虹,刘文,韩智.学习仪表盘:大数据时代的新型学习支持工具[J].现代远程教育研究,2014(3):100-107.
[16] 姜强,赵蔚,李勇帆,等.基于大数据的学习分析仪表盘研究[J].中国电化教育,2017(1):112-120.
[17] Gray J, Chaudhuri S,Bosworth A,et al. Data cube: a relational aggregation operator generalizing GROUP-BY, CROSS-TAB, and SUB-TOTALS[M]//Proceedings of the 12th International Conference on Data Engineering. New Orleans, LA, USA ,1996: 152-159).
[18] Zhang J,Tao D ,Chen M H , et al. Co-organizing the clleive joumey of inquiy with idea thread mapper [J].Jourmal of the Learming Sciences,2018 (3):1-41.
[19] Chen Q,X Yue, X Plantaz,et al. Viseq: visual analytics of learning sequence in massive open online courses[J].IEEE Trans Vis Comput Graph,2020 (3): 1622-1636.
[20] Papamitsiou Z, Economides A A. The impact of on-demand metacognitive help on effortful behaviour: a longitudinal study using task-related visual analytics[J].Journal of Computer Assisted Learning ,2020(1): 109-126.
[21] 张艳霞,孙洪涛,李爽,等.数据表征学习过程及其应用——学习分析数据集国际研究综述[J].中国电化教育,2015(9):85-93.
[22] 唐丽,张一春.学习分析仪表盘:教育大数据的可视化工具[J].高等理科教育,2018(6):31-36.
[23] Faraday P. Visually critiquing web pages[C]// 6th Conference on Human Factors and the Web. University of Texas-Austin,2000.
[24] Dourado R A , Rodrigues N,Ferreira R F,et al . A teacher-facing learning analytics dashboard for process-oriented feedback in online learning[C]// LAK21: 11th International Learning Analytics and Knowledge Conference, 2021:482-489. https://doi.org/10.1145/3448139.3448187.
[25] Mejia C B, Florian R,Vatrapu S. A novel web-based approach for visualization and inspection of reading difficulties on university students[J]. IEEE Transactions on Learning Technologies,2017(1): 53-67.
[26] 杨现民, 李新,晋欣泉. 智慧课堂中的数据应用理路与策略设计[J].广西师范大学学报(哲学社会科学版),2020(5):78-87.
[27] Bodily R,Verbert K. Review of research on student-facing learning analytics dashboards and educational recommender systems[J]. IEEE Transactions on Learning Technologies,2017 (4): 405-418.
[28] Park Y,Jo I-H. Factors that affect the success of learning analytics dashboards[J]. Educational Technology Research and Development,2019 (6): 1547-1571.
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