Facilitating Student Learning with a Chatbot in an Online Math Learning Platform
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| Title: | Facilitating Student Learning with a Chatbot in an Online Math Learning Platform |
|---|---|
| Language: | English |
| Authors: | Li Cheng (ORCID |
| Source: | Journal of Educational Computing Research. 2024 62(4):907-937. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 31 |
| Publication Date: | 2024 |
| Sponsoring Agency: | National Science Foundation (NSF) National Institutes of Health (NIH) (DHHS) Institute of Education Sciences (ED) |
| Contract Number: | R44GM146483 R305N210049 R305D210031 R305A170137 R305A170243 R305A180401 R305A120125 R305R220012 2118725 2118904 1950683 1917808 1931523 1940236 1917713 1903304 1822830 1759229 1724889 1636782 1535428 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Junior High Schools Middle Schools Secondary Education High Schools |
| Descriptors: | Artificial Intelligence, Learning Management Systems, Teaching Methods, Mathematics Instruction, Middle School Students, High School Students, Mathematics Achievement, Student Interests, Conventional Instruction, Scaffolding (Teaching Technique), Student Attitudes, Computer Software, Positive Attitudes, Self Esteem |
| DOI: | 10.1177/07356331241226592 |
| ISSN: | 0735-6331 1541-4140 |
| Abstract: | Chatbots represent a promising technology for engaging students in math learning. Guided by Jerome Bruner's constructivism and Lev Vygotsky's Zone of Proximal Development, we designed and developed a chatbot that incorporates scaffolding strategies and social-emotional considerations, and we integrated it into ASSISTments, an online math learning platform. We conducted an experimental study to examine the influence of learning math with the chatbot compared to traditional learning with hints. This study involved 85 middle and high school students from three diverse school settings in the United States. The results revealed no significant differences in students' math learning performance and perceived helpfulness and interest between the chatbot and traditional hints conditions. However, students in the chatbot condition displayed significantly lower confidence in solving a similar problem after the intervention, likely due to the removal of the high level of support provided by the chatbot. Despite this, students' open responses indicated that a significantly higher number of students had positive attitudes towards chatbots. They appreciated the chatting feature, breaking down a problem into steps, and real-time support. The study concludes with a discussion of the findings and implications for chatbot designers and developers and presents avenues for future research and practice in chatbot-assisted learning. In support of Open Science, this study has been preregistered and both the data and the analysis code used in this study are publicly available at https://osf.io/am3p8/. |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2024 |
| Accession Number: | EJ1426666 |
| Database: | ERIC |
| Abstract: | Chatbots represent a promising technology for engaging students in math learning. Guided by Jerome Bruner's constructivism and Lev Vygotsky's Zone of Proximal Development, we designed and developed a chatbot that incorporates scaffolding strategies and social-emotional considerations, and we integrated it into ASSISTments, an online math learning platform. We conducted an experimental study to examine the influence of learning math with the chatbot compared to traditional learning with hints. This study involved 85 middle and high school students from three diverse school settings in the United States. The results revealed no significant differences in students' math learning performance and perceived helpfulness and interest between the chatbot and traditional hints conditions. However, students in the chatbot condition displayed significantly lower confidence in solving a similar problem after the intervention, likely due to the removal of the high level of support provided by the chatbot. Despite this, students' open responses indicated that a significantly higher number of students had positive attitudes towards chatbots. They appreciated the chatting feature, breaking down a problem into steps, and real-time support. The study concludes with a discussion of the findings and implications for chatbot designers and developers and presents avenues for future research and practice in chatbot-assisted learning. In support of Open Science, this study has been preregistered and both the data and the analysis code used in this study are publicly available at https://osf.io/am3p8/. |
|---|---|
| ISSN: | 0735-6331 1541-4140 |
| DOI: | 10.1177/07356331241226592 |
