Ateneo Laboratory for the Learning Sciences

Thesis Abstract: The main purpose of this paper is to determine the effects of frustration on learning and mastery in video games. For this study, the target population is high school students. Using an frustration-inducing game as a testbed, we will study the relationship between in-game events, frustration and learning and master; the researchers will try to determine the correlation between them. The following data gathering methods will be used to conduct the experiment: 1. biometrics, 2. video and audio recording, 3. log file analysis and, 4. survey results.
Members:
Neil Adrian B. Abendan
Joyce Villanueva
Kim Flores

Thesis Title: Detection of Frustration in Games
Abstract: To Follow
Members
Neil Abendan
Joyce Villanueva
Kim Flores

Thesis Title: Detecting Driver Anxiety
Abstract: To follow
Member:
Francis Jan P. Macam

Thesis Abstract:
Novice programmers tend to commit errors as they learn to program.  Among the time-consuming errors are non-literal errors – errors that are incorrectly addressed by compiler error messages.  In this light, the intelligent tutoring system for novice programmers has been developed to aid novice programmers in detecting non-literal errors and correcting these accordingly.  With the target audience as novice programmers in mind, we plan to improve the interfacing of the intelligent tutoring system with the users by simplifying the graphical user interface and providing a deeper analysis of the log collected by the server.  We also plan to integrate the system to the IDE BlueJ as a plug-in.  We believe that this will make debugging non-literal errors for novice programmers an easier experience.
Members:
Carlo Martinez
Joyce Rada
Javelin Magtalas

Abstract: Having finished their studies, fresh college graduates have to eventually apply for a job. More often than not, before being accepted and employed into a company, the fresh grad would have to be interviewed by the company’s HR. Without any prior experience in working for a company, the interview might be intimidating to some fresh grads. The goal of this research is to design and develop an affect-sensitive job interview simulation to help these newly-graduated students looking for a job get used to the situation and the pressure of being interviewed for a company they seek to be employed in. Through the use of a 1-on-1 interview simulation, the user may be able to personally interact with an interviewer AI. By the end of the simulation, appropriate feedback is to be given to help improve the user’s disposition. Generally, the project seeks to condition the user to not panic or become anxious as he is being interviewed.
Members:
Robert John B. Locsin
Vincent Mathieus C. Syling
Ryan Ralph B. Sibbaluca