Quantum of Choice: How learners' feedback monitoring decisions, goals and self-regulated learning skills are related

被引:21
作者
Jivet, Ioana [1 ,2 ]
Wong, Jacqueline [3 ]
Scheffel, Maren [4 ]
Torre, Manuel Valle [1 ]
Specht, Marcus [1 ]
Drachsler, Hendrik [2 ,5 ,6 ]
机构
[1] Delft Univ Technol, Delft, Netherlands
[2] Open Univ, Heerlen, Netherlands
[3] Erasmus Univ, Rotterdam, Netherlands
[4] Ruhr Univ Bochum, Bochum, Germany
[5] Goethe Univ Frankfurt, Frankfurt, Germany
[6] DIPF, Frankfurt, Germany
来源
LAK21 CONFERENCE PROCEEDINGS: THE ELEVENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE | 2021年
关键词
learning dashboard; customisable dashboard; learner goal; self-regulated learning; feedback; ANALYTICS; ACHIEVEMENT;
D O I
10.1145/3448139.3448179
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Learning analytics dashboards (LADs) are designed as feedback tools for learners, but until recently, learners rarely have had a say in how LADs are designed and what information they receive through LADs. To overcome this shortcoming, we have developed a customisable LAD for Coursera MOOCs on which learners can set goals and choose indicators to monitor. Following a mixed-methods approach, we analyse 401 learners' indicator selection behaviour in order to understand the decisions they make on the LAD and whether learner goals and self-regulated learning skills influence these decisions. We found that learners overwhelmingly chose indicators about completed activities. Goals are not associated with indicator selection behaviour, while help-seeking skills predict learners' choice of monitoring their engagement in discussions and time management skills predict learners' interest in procrastination indicators. The findings have implications for our understanding of learners' use of LADs and their design.
引用
收藏
页码:416 / 427
页数:12
相关论文
共 45 条
[1]   The Role of Achievement Goal Orientations When Studying Effect of Learning Analytics Visualizations [J].
Beheshitha, Sanam Shirazi ;
Hatala, Marek ;
Gasevic, Dragan ;
Joksimovic, Srecko .
LAK '16 CONFERENCE PROCEEDINGS: THE SIXTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE,, 2016, :54-63
[2]   Four design principles for learner dashboards that support student agency and empowerment [J].
Bennett, Liz ;
Folley, Sue .
JOURNAL OF APPLIED RESEARCH IN HIGHER EDUCATION, 2019, 12 (01) :15-26
[3]  
Bloom B. S., 1984, Handbook 1: cognitive domain
[4]   Review of Research on Student-Facing Learning Analytics Dashboards and Educational Recommender Systems [J].
Bodily, Robert ;
Verbert, Katrien .
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 2017, 10 (04) :405-418
[5]   A Matrix of Feedback for Learning [J].
Brooks, Cameron ;
Carroll, Annemaree ;
Gillies, Robyn ;
Hattie, John .
AUSTRALIAN JOURNAL OF TEACHER EDUCATION, 2019, 44 (04) :14-32
[6]   FEEDBACK AND SELF-REGULATED LEARNING - A THEORETICAL SYNTHESIS [J].
BUTLER, DL ;
WINNE, PH .
REVIEW OF EDUCATIONAL RESEARCH, 1995, 65 (03) :245-281
[7]   The development of student feedback literacy: enabling uptake of feedback [J].
Carless, David ;
Boud, David .
ASSESSMENT & EVALUATION IN HIGHER EDUCATION, 2018, 43 (08) :1315-1325
[8]   How to Design Effective Learning Analytics Indicators? A Human-Centered Design Approach [J].
Chatti, Mohamed Amine ;
Muslim, Arham ;
Guesmi, Mouadh ;
Richtscheid, Florian ;
Nasimi, Dawood ;
Shahin, Amin ;
Damera, Ritesh .
ADDRESSING GLOBAL CHALLENGES AND QUALITY EDUCATION, EC-TEL 2020, 2020, 12315 :303-317
[9]   Using learning analytics to explore help-seeking learner profiles in MOOCs [J].
Corrin, Linda ;
de Barba, Paula G. ;
Bakharia, Aneesha .
SEVENTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE (LAK'17), 2017, :424-428
[10]   Follow the Successful Crowd: Raising MOOC Completion Rates through Social Comparison at Scale [J].
Davis, Dan ;
Jivet, Ioana ;
Kizilcec, Rene F. ;
Chen, Guanliang ;
Hauff, Claudia ;
Houben, Geert-Jan .
SEVENTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE (LAK'17), 2017, :454-463