Challenges to Transferring Western Field Research Materials and Methods to a Developing World Context

Much of the research currently undertaken in the area of intelligent tutoring systems hails from Western countries. To counteract any bias that this situation produces, to gain greater representation from the rest of the world, and to produce systems and publications that take cultural factors into account, experts recognize the need for more intercultural evaluations and collaborations. For these collaborations to be successful, though, methods and materials require modification. Field work methodologies used in developed countries have to be nuanced when transferred to developing world contexts. In specific, the paper describes five challenges that researchers must address in the transfer process: technology adoption, school support, infrastructure, student culture, and force majeure

Transitions of Affective States in an Intelligent Tutoring System

This paper aims to determine the natural transitions that take place among students‘ affective states while using SQL-Tutor, a constraint-based intelligent tutor that teaches Structured Query Language (SQL). Intelligent tutoring systems, such as SQL-Tutor, have been used by various institutions to overcome the difficulties of students in learning difficult subject matter. In this paper, the researchers intend to determine how an affective state at a given time influences the affective state at a later time. Likely transitions of affective states were mined from the observation files gathered from students during interaction with the tutor. The researchers were able to identify several affective transitions that were unlikely to occur. Identifying these natural transitions is a stepping stone towards designing interventions that might help sustain desirable affective states, encourage productive affective transitions and mitigate states and transitions that may be deemed detrimental to learning

Monitoring Novice Programmer Affect and Behaviors to Identify Learning Bottlenecks

We analyze student affect data in order to locate bottlenecks in an introductory programming course. By tracking students’ affective states and behaviors over five laboratory sessions distributed over nine weeks, we find that students exhibit a significantly greater amount of confusion when expected to implement object-oriented constructs such as constructors and object interaction. When asked to undertake an exercise similar in scope with a previous exercise, students expend less time and effort on the exercise. They exhibit less flow and frustration, and spend more time on off-task behaviors

Use of Unsupervised Clustering to Characterize Learner Behaviors and Affective States while Using an Intelligent Tutoring System

This paper presents results from a preliminary analysis of interaction and human observation data gathered from students using an Aplusix, an intelligent tutoring system for algebra. Towards the development of automatic detectors of behavior and affect, this study tried to determine whether it was possible to identify distinct groups of students based on interaction logs alone. Using unsupervised clustering, we were able to identify that student behaviors within the software cluster into two categories, Clusters 0 and 1, associated with differing higher-level behaviors and affective states. Cluster 0 tended to reflect more collaborative work, whereas Cluster 1 reflected more solitary work. Cluster 1 students tended to exhibit more flow, suggesting that students in flow tend to work in a more individual fashion. An examination of the keystrokes used by each group showed that Cluster 0 used the arrow keys and cursor keys significantly more than Cluster 1. The Cluster 1, on the other hand, tended to type more mathematical operators or use the duplicate command more frequently than Cluster 0. This implies that frequent use of mathematical operators and frequent duplication of the problem may be evidence of flow within Aplusix

Gathering Behaviors and Affective States of Learners Using Educational Software: Challenges to Research in an Emerging Economy

Much of the research currently undertaken in the area of intelligent tutoring systems hails from the Western countries. To counteract any bias that this situation produces, to gain greater representation from the rest of the world, and to produce systems and publications that take cultural factors in to account, experts recognize the need for more intercultural evaluations and collaborations. To inform researchers planning field studies in developing countries, this paper discusses five challenges that researchers must address: technology adoption, school support, infrastructure, student culture, and force majeur

Exploring a Methodology for Automatically Detecting Positive or Negative Events in a Virtual Racing Game

We describe a work-in-progress that attempts to detect anxiety in drivers while exposed to a virtual racing game. The detection system is a combination of two Nintendo Wii Balance Boards, parallel video recording of in-game events and facial expressions, and the OCZ Technology\u27s Neural Impulse Actuator (NIA) braincontrolled headset. We attempt to establish a relationship among the various physiological and physical signals with occurrences of anxiety as coded by human observers when viewing video recordings of facial expressions

Exploring the Relationship between Novice Programmer Confusion and Achievement

Using a discovery-with-models approach, we study the relationships between novice Java programmers’ experiences of confusion and their achievement, as measured through their midterm examination scores. Two coders manually labeled samples of student compilation logs with whether they represent a student who was confused. From the labeled data, we built a model that we used to label the entire data set. We then analysed the relationship between patterns of confusion and non-confusion over time, and students’ midterm scores. We found that, in accordance with prior findings, prolonged confusion is associated with poorer student achievement. However, confusion which is resolved is associated with statistically significantly better midterm performance than never being confused at all

Modeling the affective states of students using an intelligent tutoring system for algebra

The medium-term goal of this project is to implement an emotionally intelligent learning companion that will provide algebra students with encouragement and support. To this end, this study sought to improve upon existing models of affect of students using Aplusix, an intelligent tutor for algebra. Continuing earlier work, this model was a refined analysis of student interaction logs with the ITS using linear regression. Unfortunately, the models produced had low correlations with the data