Enhancing learning outcomes through self-regulated learning support with an Open Learner Model

被引:57
作者
Long, Yanjin [1 ]
Aleven, Vincent [2 ]
机构
[1] Univ Pittsburgh, Learning Res & Dev Ctr, 3939 OHara St, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Human Comp Interact Inst, 5000 Forbes Ave, Pittsburgh, PA 15213 USA
基金
美国国家科学基金会;
关键词
Open Learner Model; Self-assessment; Making problem selection decisions; Intelligent tutoring system; Learner control; Self-regulated learning; Classroom experiment; SHARED CONTROL; INTELLIGENT; MOTIVATION; FRAMEWORK; REGION; CHOICE; TIME;
D O I
10.1007/s11257-016-9186-6
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
Open Learner Models (OLMs) have great potential to support students' Self-Regulated Learning (SRL) in Intelligent Tutoring Systems (ITSs). Yet few classroom experiments have been conducted to empirically evaluate whether and how an OLM can enhance students' domain level learning outcomes through the scaffolding of SRL processes in an ITS. In two classroom experiments with a total of 302 7th- and 8th-grade students, we investigated the effect of (a) an OLM that supports students' self-assessment of their equation-solving skills and (b) shared control over problem selection, on students' equation-solving abilities, enjoyment of learning with the tutor, self-assessment accuracy, and problem selection decisions. In the first, smaller experiment, the hypothesized main effect of the OLM on students' learning outcomes was confirmed; we found no main effect of shared control of problem selection, nor an interaction. In the second, larger experiment, the hypothesized main effects were not confirmed, but we found an interaction such that the students who had access to the OLM learned significantly better equation-solving skills than their counterparts when shared control over problem selection was offered in the system. Thus, the two experiments support the notion that an OLM can enhance students' domain-level learning outcomes through scaffolding of SRL processes, and are among the first in-vivo classroom experiments to do so. They suggest that an OLM is especially effective if it is designed to support multiple SRL processes.
引用
收藏
页码:55 / 88
页数:34
相关论文
共 78 条
[1]
Aleven V, 2000, LECT NOTES COMPUT SC, V1839, P292
[2]
Aleven V., 2009, International Journal of Artificial Intelligence and Education, V19, P105
[3]
Example-Tracing Tutors: Intelligent Tutor Development for Non-programmers [J].
Aleven V. ;
McLaren B.M. ;
Sewall J. ;
Van Velsen M. ;
Popescu O. ;
Demi S. ;
Ringenberg M. ;
Koedinger K.R. .
International Journal of Artificial Intelligence in Education, 2016, 26 (01) :224-269
[4]
Aleven V, 2010, STUD COMPUT INTELL, V308, P33
[5]
Cognitive tutors: Lessons learned [J].
Anderson, JR ;
Corbett, AT ;
Koedinger, KR ;
Pelletier, R .
JOURNAL OF THE LEARNING SCIENCES, 1995, 4 (02) :167-207
[6]
[Anonymous], 2013, Design recommendations for adaptive intelligent tutoring systems
[7]
[Anonymous], P 23 C US MOD AD PER
[8]
Arroyo I, 2007, FRONT ARTIF INTEL AP, V158, P195
[9]
OPTIMIZING LEARNING OF A SECOND-LANGUAGE VOCABULARY [J].
ATKINSON, RC .
JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 1972, 96 (01) :124-&
[10]
Azevedo R., 2013, International handbook of metacognition and learning technologies