ASSISTments Longitudinal Data Mining Competition Special Issue: A Preface
Year: 2020
Type: article
Abstract: This special issue includes papers from some of the leading competitors in the ASSISTments Longitudinal Data Mining Competition 2017, as well as some research from non-competitors, using the same data set. In this competition, participants attempted to predict whether students would choose a career in a STEM field or not, making this prediction using a click-stream dataset from middle school students working on math assignments inside ASSISTments, an online tutoring platform. At the conclusion of the competition on December 3rd, 2017, there were 202 participants, 74 of whom submitted predictions at least once. In this special issue, some of the leading competitors present their results and what they have learned about the link between behavior in online learning and future STEM career development.
Institutions: Worcester Polytechnic Institute, University of Pennsylvania
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
Awards: Collaborative Research: Precision Learning: Data-Driven Experimentation of Learning Theories using Internet-of-Videos, G1717380892, BD Spokes: Spoke: NORTHEAST: Collaborative: Grand Challenges for Data-Driven Education, Improving Formative Assessment Practices: Using Learning Trajectories to Develop Resources that Support Teacher Instructional Practice and Student Learning in CMP2, Putting Teachers in the Driver's Seat: Using Machine Learning to Personalize Interactions with Students (DRIVER-SEAT), Collaborative Research: Student Affect Detection and Intervention with Teachers in the Loop, Evaluating the Effectiveness of ASSISTments for Improving Math Achievement, G3249482350, The Efficacy of From Here to There: A Dynamic Technology for Improving Algebraic Understanding, CIF21 DIBBs: PD: Enhancing and Personalizing Educational Resources through Tools for Experimentation, An Efficacy Study of Online Mathematics Homework Support: An Evaluation of the ASSISTments Formative Assessment and Tutoring Platform, Collaborative Research: The Downside of Perseverance--Investigating and Moving Students Beyond Unproductive Persistence, BD Spokes: Spoke: NORTHEAST: Collaborative: Grand Challenges for Data-Driven Education, Personalizing Mathematics to Maximize Relevance and Skill for Tomorrow's STEM Workforce, BD Spokes: Spoke: NORTHEAST: Collaborative: Grand Challenges for Data-Driven Education, Empirical Research, Contextual Research: Taking advantage of Cognitive Science Principles: Adding to a Computer-Based Tutor an Automatic Reassessment and Relearning System, SI2-SSE: Adding Research Accounts to the ASSISTments' Platform: Helping Researchers Do Randomized Controlled Studies with Thousands of Students, IUSE: EHR: Improving Undergraduate Algorithms Instructions with Online Feedback, National Research & Development Center on Cognition and Mathematics Instruction, Making Math Tutors More Engaging and Effective through Interaction Design Patterns and Educational Data Mining, Collaborative Research: Frameworks: Cyber Infrastructure for Shared Algorithmic and Experimental Research in Online Learning, G8876996369, Research: Predicting STEM Career Choice from Computational Indicators of Student Engagement within Middle School Mathematics Classes, G964869846
OpenAlex ID: W3085763522