ERIC Number: ED596603
Record Type: Non-Journal
Publication Date: 2017-Jun
Pages: 6
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Linking Language to Math Success in an On-Line Course
Crossley, Scott; Barnes, Tiffany; Lynch, Collin; McNamara, Danielle S.
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (10th, Wuhan, China, Jun 25-28, 2017)
This study takes a novel approach toward understanding success in a math course by examining the linguistic features and affect of students' language production within a blended (with both on-line and traditional face to face instruction) undergraduate course (n=158) on discrete mathematics. Three linear effects models were compared: (a) a baseline linear model including nonlinguistic fixed effects, (b) a model including only linguistic factors, (c) a model including both linguistic and non-linguistic effects. The best model (c) explained 16% of the variance of final course scores, revealing significant effects for one non-linguistic feature (days on the system) and two linguistic features ("Number of dependents per prepositional object nominal and Sentence linking connectives"). One non-linguistic factor ("Is a peer tutor") and two linguistic variables ("Words related to self and Words related to tool use") demonstrated marginal significance. The findings indicate that language proficiency is strongly linked to math performance such that more complex syntactic structures and fewer explicit cohesion devices equate to higher course performance. The linguistic model also indicated that less self-centered students and students using words related to tool use were more successful. In addition, the results indicate that students that are more active in on-line discussion forums are more likely to be successful. [For the full proceedings, see ED596512.]
Descriptors: Success, Mathematics Instruction, Language Usage, Blended Learning, Conventional Instruction, Undergraduate Students, College Mathematics, Models, Scores, Peer Teaching, Data Collection, Data Analysis, Language Proficiency, Syntax, Computer Mediated Communication, Educational Technology, Technology Uses in Education, Online Courses
International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Publication Type: Reports - Research; Speeches/Meeting Papers
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Identifiers - Location: North Carolina
Grant or Contract Numbers: DRL1418378
Author Affiliations: N/A