Ateneo Laboratory for the Learning Sciences

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

Thesis Abstract:
Brain-computer interfaces (BCIs), a communication link between the brain of a user and a computer, have found their way into the gaming industry. This paper is a continuation to a previously conducted thesis that developed a prototype of an affect-sensitive game. It will address several questions, most prominently concerning the proper utilization of the OCZ Neural-Impulse Actuator in order to create affective elements that contribute to the development of an affective game. After creating a stable plot for the game, we will explore the possibilities of designing BCI-dependent or affect-sensitive agents that change accordingly in accordance to the user’s brain waves.
Members:
Tricia Monsod
Jason King Li

Abstract:
The purpose of this thesis is to determine fear using the signals recorded by a Brain-Computer Interface (BCI) device and incorporate this information into an affect-sensitive horror game. The researchers will use the information regarding fear from the player so that they would be able to create and manipulate different states of game play to enhance the game experience.
Members:
Gabriel Matias
Izzabella Perez
Tiffang Kang

Thesis Title: Transitions Between Affective States and Its Relationship to Learner Performance in an Intelligent Tutoring System
Thesis Abstract:
As affect is associated with cognition and learning, the paper aims to determine how affective states relate to student performance within SQL-Tutor, a constraint-based tutor in Structured Query Language (SQL) from the University of Canterbury, New Zealand. Specifically, the study will analyze relationship between dynamics of affective transitions and learning. Using user action log files and human observation data gathered from MIS students, the researcher intends to determine how an affective state at a given time influences the affective state at a later time. The researcher will find the likely transitions of affective states by mining through the observation files. Its relationship to student performance will then be analyzed using the action log files obtained from the ITS.
Member:
Thea Faye G. Guia