Analytics of scaffold compliance for self-regulated learning

被引:1
|
作者
Saint, John [1 ]
Fan, Yizhou [2 ]
Gasevic, Dragan [3 ]
机构
[1] Regents Univ London, London, England
[2] Peking Univ, Grad Sch Educ, Beijing, Peoples R China
[3] Monash Univ, Fac Informat Technol, Melbourne, Vic, Australia
基金
英国经济与社会研究理事会; 澳大利亚研究理事会;
关键词
Learning Analytics; Scaffolding; Scaffolding Compliance; Self-Regulated; Learning; Process Mining; Clustering; METACOGNITIVE PROMPTS;
D O I
10.1145/3636555.3636887
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The shift toward digitally-based education has emphasised the need for learners to have strong skills for self-regulated learning (SRL). The use of scaffolding prompts is seen as an effective way to stimulate SRL and enhance academic outcomes. A key aspect of SRL scaffolding prompts is the degree to which they are complied to by students. Compliance is a complex concept, one that is further complicated by the nature of scaffold design in the context of adaptability. These nuances notwithstanding, scaffold compliance demands specific exploration. To that end, we conducted a study in which we: 1) focused specifically on scaffolding interaction behaviour in a timed online assessment task, as opposed to the broader interaction with non-scaffolding artefacts; 2) identified distinct scaffold interaction patterns in the context of compliance and non-compliance to scaffold design; 3) analysed how groups of learners traverse compliant and non-compliant interaction behaviours and engage in SRL processes in response to a sequence of timed and personalised SRL-informed scaffold prompts. We found that scaffold interactions fell into two categories of compliance and non-compliance, and whilst there was a healthy engagement with compliance, it does ebb and flow during an online timed assessment.
引用
收藏
页码:326 / 337
页数:12
相关论文
共 50 条
  • [41] Promoting higher education students' self-regulated learning through learning analytics: A qualitative study
    Kleimola, Riina
    Hirsto, Laura
    Ruokamo, Heli
    EDUCATION AND INFORMATION TECHNOLOGIES, 2025, 30 (04) : 4959 - 4986
  • [42] Effects of a mobile self-regulated learning approach on students' learning achievements and self-regulated learning skills
    Zheng, Lanqin
    Li, Xin
    Chen, Fengying
    INNOVATIONS IN EDUCATION AND TEACHING INTERNATIONAL, 2018, 55 (06) : 616 - 624
  • [43] Impact of learning analytics feedback on self-regulated learning: Triangulating behavioural logs with students' recall
    Lim, Lisa-Angelique
    Gasevic, Dragan
    Matcha, Wannisa
    Uzir, Nora'Ayu Ahmad
    Dawson, Shane
    LAK21 CONFERENCE PROCEEDINGS: THE ELEVENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, 2021, : 364 - 374
  • [44] Assessment of the usability of a Learning Analytics resource dedicated to promoting Self-Regulated Learning in Flipped Classroom
    Sedraz Silva, Joao Carlos
    de Souza, Fernando da Fonseca
    Cavalcanti Ramos, Jorge Luis
    Rodrigues, Rodrigo Lins
    Zambom, Erik de Gouveia
    Cavalcanti, Aldo
    REVISTA LATINOAMERICANA DE TECNOLOGIA EDUCATIVA-RELATEC, 2018, 17 (02): : 9 - 23
  • [45] Using learning analytics to explore self-regulated learning in flipped blended learning music teacher education
    Montgomery, Amanda P.
    Mousavi, Amin
    Carbonaro, Michael
    Hayward, Denyse V.
    Dunn, William
    BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY, 2019, 50 (01) : 114 - 127
  • [46] Are profiles of self-regulated learning and intelligence mindsets related to students' self-regulated learning and achievement?
    Hertel, Silke
    Reschke, Katharina
    Karlen, Yves
    LEARNING AND INSTRUCTION, 2024, 90
  • [47] A self-regulated learning system with scaffolding support for self-regulated e/m-learning
    Shih, KP
    Chang, CY
    Chen, HC
    Wang, SS
    ITRE 2005: 3RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY: RESEARCH AND EDUCATION, PROCEEDINGS, 2005, : 30 - 34
  • [48] Understanding self-regulated learning: thoughts from attending the Self-Regulated Learning Symposium in Shimonoseki
    Thornton, Katherine
    STUDIES IN SELF-ACCESS LEARNING JOURNAL, 2014, 5 (04): : 460 - 465
  • [49] Application of learning analytics to study the accuracy of self-reported working patterns in self-regulated learning questionnaires
    Uguina Gadella, Lucia
    Estevez-Ayres, Iria
    Arias Fisteus, Jesus
    Delgado-Kloos, Carlos
    PROCEEDINGS OF THE 2020 IEEE GLOBAL ENGINEERING EDUCATION CONFERENCE (EDUCON 2020), 2020, : 1201 - 1205
  • [50] Temporal Analytics of Workplace-Based Assessment Data to Support Self-regulated Learning
    Piotrkowicz, Alicja
    Dimitrova, Vania
    Roberts, Trudie E.
    LIFELONG TECHNOLOGY-ENHANCED LEARNING, EC-TEL 2018, 2018, 11082 : 570 - 574