As evidence grows supporting the importance of non-cognitive
factors in learning, computer-assisted learning platforms increasingly
incorporate non-academic interventions to influence student
learning and learning related-behaviors. Non-cognitive interventions
often attempt to influence students’ mindset, motivation, or
metacognitive reflection to impact learning behaviors and outcomes.
In the current paper, we analyze data from five experiments, involving
seven treatment conditions embedded in mastery-based
learning activities hosted on a computer-assisted learning platform
focused on middle school mathematics. Each treatment condition
embodied a specific non-cognitive theoretical perspective. Over
seven school years, 20,472 students participated in the experiments.
We estimated the effects of each treatment condition on students’
response time, hint usage, likelihood of mastering knowledge components,
learning efficiency, and post-tests performance. Our analyses
reveal a mix of both positive and negative treatment effects
on student learning behaviors and performance. Few interventions
impacted learning as assessed by the post-tests. These findings
highlight the difficulty in positively influencing student learning
behaviors and outcomes using non-cognitive interventions.
more »
« less
Impact of Non-Cognitive Interventions on Student Learning Behaviors and Outcomes: An analysis of seven large-scale experimental inventions
As evidence grows supporting the importance of non-cognitive factors in learning, computer-assisted learning platforms increasingly incorporate non-academic interventions to influence student learning and learning related-behaviors. Non-cognitive interventions often attempt to influence students’ mindset, motivation, or metacognitive reflection to impact learning behaviors and outcomes. In the current paper, we analyze data from five experiments, involving seven treatment conditions embedded in mastery-based learning activities hosted on a computer-assisted learning platform focused on middle school mathematics. Each treatment condition embodied a specific non-cognitive theoretical perspective. Over seven school years, 20,472 students participated in the experiments. We estimated the effects of each treatment condition on students’ response time, hint usage, likelihood of mastering knowledge components, learning efficiency, and post-tests performance. Our analyses reveal a mix of both positive and negative treatment effects on student learning behaviors and performance. Few interventions impacted learning as assessed by the post-tests. These findings highlight the difficulty in positively influencing student learning behaviors and outcomes using non-cognitive interventions.
more »
« less
- Award ID(s):
- 1931523
- PAR ID:
- 10443563
- Date Published:
- Journal Name:
- LAK23: 13th International Learning Analytics and Knowledge Conference
- Page Range / eLocation ID:
- 165 to 174
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Management education holds promise for addressing deficiencies in interuniversity science, technology, engineering, and mathematics (STEM), as well as sustainability curricula. Accordingly, we designed, developed, implemented, and longitudinally evaluated interdisciplinary STEM-based curricula in the United States. Students in five sections of business management courses and two sections of STEM courses received a STEM-based sustainability intervention (i.e., an interdisciplinary STEM and sustainability module). To assess student outcomes following the intervention and examine the feasibility of cognitive mapping as a student learning assessment tool, we implemented a pre- and post-course modified cognitive mapping assessment in treatment and comparison courses. To interpret the results, we ran descriptives, correlations, paired sample t tests, and principal component analysis. The t tests suggest that when all coding categories are considered, those participating in curricular interventions listed significantly more sustainability terms. The principal component analysis results demonstrate that treatment courses improved variability explained by 7.23% between pre- and post-tests but declined by 8.22% for comparison courses. Overall, linkages became stronger between parent code categories for treatment courses and weaker for comparison courses. These findings add to existing research related to cognitive mapping and demonstrate the ability of the method to capture changes in student outcomes after exposure to STEM-based sustainability curriculum.more » « less
-
This study aimed to compare the effects of immersive virtual reality (IVR) videos and 2D educational videos on cognitive (i.e. conceptual knowledge) and non-cognitive (i.e. self-efficacy) learning outcomes. Fifty-three students from an all-girls middle school learned about humans’ impact on the ocean through either IVR videos, using a virtual reality (VR) headset, or through 2D videos, using a computer monitor. Results replicate previous findings suggesting that conceptual knowledge gains between IVR and desktop learning experiences is not significant. Also, results show that participants who watched IVR videos reported higher self-efficacy scores and expressed higher feelings of presence than participants who watched the same videos using a computer monitor. Finally, further analyses revealed that the feeling of presence mediated both cognitive and non-cognitive learning outcomes.more » « less
-
Cognitive control and rule learning are two important mechanisms that explain how goals influence behavior and how knowledge is acquired. These mechanisms are studied heavily in cognitive science literature within highly controlled tasks to understand human cognition. Although they are closely linked to the student behaviors that are often studied within intelligent tutoring systems (ITS), their direct effects on learning have not been explored. Understanding these underlying cognitive mechanisms of beneficial and harmful student behaviors can provide deeper insight into detecting such behaviors and improve predictive models of student learning. In this paper, we present a thinkaloud study where we asked students to narrate their thought processes while solving probability problems in ASSISTments. Students are randomly assigned to one of two conditions that are designed to induce the two modes of cognitive control based on the Dual Mechanisms of Control framework. We also observe how the students go through the phases of rule learning as defined in a rule learning paradigm. We discuss the effects of these different mechanisms on learning, and how the information they provide can be used in student modeling.more » « less
-
Cognitive control and rule learning are two important mechanisms that explain how goals influence behavior and how knowledge is acquired. These mechanisms are studied heavily in cognitive science literature within highly controlled tasks to understand human cognition. Although they are closely linked to the student behaviors that are often studied within intelligent tutoring systems (ITS), their direct effects on learning have not been explored. Understanding these underlying cognitive mechanisms of beneficial and harmful student behaviors can provide deeper insight into detecting such behaviors and improve predictive models of student learning. In this paper, we present a thinkaloud study where we asked students to narrate their thought processes while solving probability problems in ASSISTments. Students are randomly assigned to one of two conditions that are designed to induce the two modes of cognitive control based on the Dual Mechanisms of Control framework. We also observe how the students go through the phases of rule learning as defined in a rule learning paradigm. We discuss the effects of these different mechanisms on learning, and how the information they provide can be used in student modeling.more » « less