Using archived student data for middle and high school students’ mathematics-focused intelligent tutoring system (ITS) learning collected across a school year, this study explores situational, achievement-goal latent profile membership and the stability of these profiles with respect to student demographics and dispositional achievement goal scores. Over 65% of students changed situational profile membership at some time during the school year. Start-of-year dispositional motivation scores were not related to whether students remained in the same profile across all unit-level measurements. Grade level was predictive of profile stability. Findings from the present study should shed light on how in-the-moment student motivation fluctuates while students are engaged in ITS math learning. Present findings have potential to inform motivation interventions designed for ITS math learning.
more »
« less
The nature of achievement goal motivation profiles: Exploring situational motivation in an algebra-focused intelligent tutoring system.
Building on recent work related to measuring situational, in-the-moment motivation and the stability of motivation profiles, this study explores the nature of situational motivation profiles constructed with measurements of achievement goals during middle and high school students’ algebra-focused intelligent tutoring system (ITS) learning during an academic semester. The results of multi-level profile analyses nesting multiple timepoints within students indicates the presence of four distinct profiles, with similar characteristics to those found in previous studies on dispositional achievement goals in mathematics for similar-aged students. Present findings have potential implications for designing effective motivation interventions during ITS learning.
more »
« less
- Award ID(s):
- 1934745
- PAR ID:
- 10291640
- Date Published:
- Journal Name:
- Proceedings of the 2nd Learner Data Institute Workshop at the Fourteenth International Conference on Educational Data Mining
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
SITE (Ed.)Persons with learning disabilities (LD) are underrepresented in computer science and information technology fields despite the explosion of related career opportunities and interest. In this study, we examine the use of pair programming as a collaborative intervention in with computer programming and compare students with learning disabilities to students who do not have learning disabilities. We concentrate on situational motivation constructs which tap into the desire to meet goals and acquire skills. We find that students with LD and similar students without LD fare the same. For the both groups, three of the four situational motivation subscales increase after the introduction of pair programming. The use of pair programming holds promise as an educational intervention for all students including those with learning disabilities.more » « less
-
null (Ed.)School closures during the COVID-19 pandemic presented a threat to student learning and motivation. Suspension of achievement testing created a barrier to understanding the extent of this threat. Leveraging data from a mathematics learning software as a substitute assessment, we found that students had lower engagement with the software during the pandemic, but students who did engage had increased performance. Students also experienced changes in motivation: lowered mathematics expectancy, but also lower emotional cost for mathematics. Results illustrate the potential and pitfalls of using educational technology data in lieu of traditional assessments and draw attention to access and motivation during at-home schooling.more » « less
-
Students, instructors, and policy makers are in need of research-based recommendations for supporting students’ motivation to pursue STEM fields. The present study addressed this need by examining relations between perceived motivational supports, year-long trajectories of expectancy for success and three task values, and grades among students ( N = 1,021) in a large, gateway engineering course. Results indicated that students with higher motivation at the beginning of the year tended to perceive their class as more motivationally supportive. Controlling for relations between initial motivation and perceptions, perceived instructional supports for mastery goals, autonomy, and competence predicted more positive trajectories of all three task values. Conversely, higher perceived instructor performance goals negatively predicted grades and the slopes of self-efficacy and interest value. Results contribute key understanding about the interconnectedness of individual motivation and climate perceptions, while indicating the importance students place on certain motivationally supportive practices in promoting students’ STEM motivation trajectories.more » « less
-
Success in online and blended courses requires engaging in self-regulated learning (SRL), especially for challenging STEM disciplines, such as physics. This involves students planning how they will navigate course assignments and activities, setting goals for completion, monitoring their progress and content understanding, and reflecting on how they completed each assignment. Based on Winne & Hadwin’s COPES model, SRL is a series of events that temporally unfold during learning, impacted by changing internal and external factors, such as goal orientation and content difficulty. Thus, as goal orientation and content difficulty change throughout a course, so might students’ use of SRL processes. This paper studies how students’ SRL behavior and achievement goal orientation change over time in a large ( N = 250) college introductory level physics course taught online. Students’ achievement goal orientation was measured by repeated administration of the achievement goals questionnaire-revised (AGQ-R). Students’ SRL behavior was measured by analyzing their clickstream event traces interacting with online learning modules via a combination of trace clustering and process mining. Event traces were first divided into groups similar in nature using agglomerative clustering, with similarity between traces determined based on a set of derived characteristics most reflective of students’ SRL processes. We then generated causal nets for each cluster of traces via process mining and interpreted the underlying behavior and strategy of each causal net according to the COPES SRL framework. We then measured the frequency at which students adopted each causal net and assessed whether the adoption of different causal nets was associated with responses to the AGQ-R. By repeating the analysis for three sets of online learning modules assigned at the beginning, middle, and end of the semester, we examined how the frequency of each causal net changed over time, and how the change correlated with changes to the AGQ-R responses. Results have implications for measuring the temporal nature of SRL during online learning, as well as the factors impacting the use of SRL processes in an online physics course. Results also provide guidance for developing online instructional materials that foster effective SRL for students with different motivational profiles.more » « less
An official website of the United States government

