Mid-Year Meeting (2020)

The Learner Data Institute is funded by The National Science Foundation

Agenda + Materials

[All times are Central Time (UTC−05:00) in the USA.]

July 10, 2020 (morning) — online

Held in conjunction with the First LDI Workshop @ EDM 2020


9:00 - 10:00AM: Introduction & Overview (Vasile Rus & Stephen Fancsali) [Presentation]

9:30 - 9:35AM: Break

9:35 - 10:05AM: Invited Speaker: Valerie Purdie-Greenaway, Columbia University - "Closing racial achievement gaps: What social psychology interventions in the classroom can teach us about equity in data sciences" [Presentation]

10:05 - 10:15AM: Break

10:15 - 10:45AM: Invited Speaker: Jared Bernstein, Analytic Measures, Inc. - "Automated Measures of Spoken Language for Monitoring, Adaptation, & Diagnosis" [Presentation]

Abstract: Presentation introduces the kinds of information that can be extracted from spoken interactions and notes how such information may be useful in Adaptive Instruction Systems. We describe the technology, task structure, and accuracy of three assessments (spanning 1999-2020) which score spoken performances to measure second language proficiency, basic reading, and mental status. The application of these methods to improvement of AISs is also presented.

10:45 - 11:00AM: Break

11:00 - 11:45AM: "FireHose Presentations" - Concrete Tasks (90-seconds/speaker)

      • Automated Methods to Use Learner Data to Infer and Improve Domain Models of Learning (P. Pavlik)

      • Student Strategy Prediction (D. Venugopal & V. Rus)

      • Autoencoders for Educational Assessment (D. Bowman)

      • Scaling Empirical Refinement of Domain Models & Instructional Design (S. Fancsali)

      • Extraction and Simulation of Causal Arguments for Nominal Reproducibility and Replicability (ESCANoRR) (A. Olney)

      • ENGAGE SmartClassroom: An IoT supported Data Collection System for Tracking Student Behavior Across time in Public Education (L. Casey & S. Elswick)

      • AI methods to support accurate root cause analysis of learner data (R. Sottilare)

      • EdgeAI: Context-aware personalized recommender models by utilizing users’ wearables, IoTs, and smart devices at edge implemented with transfer learning (B. Morshed)

      • Using Big Data to Develop a New Method for Examining the Relationship between Student Socioeconomic Status and Achievement (T. Zoblotsky)

      • Developing Interactive Coding Tool for Learning Data (Z. Cai & D. Shaffer)

      • Talk Shop: A Thought Experiment (D. Morrison)

      • Human-Technology Frontier (A. Tawfik)

      • Systematically Evaluate AutoTutor Rules (X. Hu)

      • AutoTutor for Adult Reading Comprehension Training (A. Graesser)

      • Variability in Motivational Feedback Systems During Learning with Intelligent Tutoring Systems (ITS) (C. Mueller & L. Harrell-Williams)

      • Exploring and Assessing the Development of Students’ Argumentative Writing Skills (J. Sabatini)

      • Machine Reading for Understanding Textbooks (A. Olney)

11:45AM - 1:00PM: Lunch Break

In the afternoon, we convened the First LDI Workshop @ EDM 2020: Big Data, Research Challenges, and Science Convergence in Educational Data Science.