AAAI Publications, Twenty-Ninth AAAI Conference on Artificial Intelligence

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A Stackelberg Game Approach for Incentivizing Participation in Online Educational Forums with Heterogeneous Student Population
Rohith Dwarakanath Vallam, Priyanka Bhatt, Debmalya Mandal, Narahari Y.

Last modified: 2015-02-16

Abstract


Increased interest in web-based education has spurred the proliferation of online learning environments. However, these platforms suffer from high dropout rates due to lack of sustained motivation among the students taking the course. In an effort to address this problem, we propose an incentive-based, instructor-driven approach to orchestrate the interactions in online educational forums (OEFs). Our approach takes into account the heterogeneity in skills among the students as well as the limited budget available to the instructor. We first analytically model OEFs in a non-strategic setting using ideas from lumpable continuous time Markov chains and compute expected aggregate transient net-rewards for the instructor and the students. We next consider a strategic setting where we use the rewards computed above to set up a mixed-integer linear program which views an OEF as a single-leader-multiple-followers Stackelberg game and recommends an optimal plan to the instructor for maximizing student participation. Our experimental results reveal several interesting phenomena including a striking non-monotonicity in the level of participation of students vis-a-vis the instructor's arrival rate.

Keywords


online educational forums; incentive design; Stackelberg game; continuous time Markov chains; mixed integer linear program; instructor-student interactions

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