Jessica O. Sugay

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We investigate the relationship between a student’s affect and how he or she chooses to use a simulation problem-solving environment, using quantitative field observations. Within the environment studied, many students were observed gaming the system (cf. Baker et al, 2004), while few students engaged in off-task behavior. We analyze which affective states(More)
We study which observable affective states and behaviors relate to students' achievement within a CS1 programming course. To this end, we use a combination of human observation, midterm test scores, and logs of student interactions with the compiler within an Integrated Development Environment (IDE). We find that confusion, boredom and engagement in(More)
A motivationally-aware version of the Ecolab system was developed with the aim of improving the learners’ motivation. To gain some insight into the effects of motivational modeling on students’ affective states, we observed the affect of 180 students interacting with either Ecolab or M-Ecolab. The affective states considered were based on existing coding(More)
We compare the affect associated with an intelligent tutoring environment, Aplusix, and a simulations problem solving game, The Incredible Machine, to determine whether students experience significantly better affect in an educational game than in an ITS. We find that affect was, on the whole, better in Aplusix than it was in The Incredible Machine.(More)
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(More)
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(More)
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(More)
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(More)
We investigated the interplay between confusion and in-game behavior among students using Newton’s Playground (NP), a computer game for physics. We gathered data from 48 public high school students in the Philippines. Upon analyzing quantitative field observations and interaction logs generated by NP, we found that confusion among students was negatively(More)
This paper presents some of the challenges encountered by a field research team when deploying an educational game for Physics. These included problems with site infrastructure and institutional support, logistical challenges, compliance with ethics requirements, launch delays, and student inattention or misunderstanding of directions. The paper shares(More)