Traditional software development relied heavily on manual coding handled solely by human programmers, assisted by smart editors and IDEs. With the rise of Gen AI, much of the coding and debugging process has been automated, significantly improving productivity. For instance, Amazon reported saving 4,500 man-years and 260 million using its AI tool in 2024. This shift raises questions for computing education: What skills should students learn if coding can be automated?

One of the Sustainable Development Goals (SDGs) established by the United Nations is Quality Education, specifically aiming to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all (SDG 4). This goal emphasizes the provision of education that is accessible, fair, and of high quality to individuals regardless of their background or circumstances. Innovative technologies, such as Generative Al, offer new prospects for enhancing both the access to and quality of education. However, they also introduce new challenges that could potentially have negative impacts. This panel aims to provide a platform for sharing international perspectives, with panellists from different countries, and for exchanging ideas, experiences, and practices towards achieving SDG 4. The discussion will focus on three main areas: 1) global challenges in achieving inclusive and equitable quality education; 2) good practices in promoting inclusive and equitable education with digital technology; 3) the impact of innovative technologies, such as Generative Al in promoting access to quality education. The goal of this panel is to promote research in inclusive and equitable education within APSCE by highlighting the significance of digital technology as a catalyst for change and exploring strategies to realize quality education for all.

This study characterizes linguistic sophistication within university-based online courses using Learning Management Systems (LMS) across various academic disciplines. The research employs natural language processing tools to extract detailed linguistic features from student discussion posts and utilizes Principal Components Analysis (PCA) to identify distinct linguistic profiles. These profiles are analyzed to understand how linguistic sophistication varies across different educational contexts, specifically among various schools and courses. Subsequent cluster analysis reveals statistically significant distinct groups based on linguistic attributes. Despite the comprehensive analysis, the study did not establish significant predictive models linking linguistic sophistication to any direct educational outcomes. Instead, the findings highlight significant differences in language use across disciplines, suggesting that each academic field may have unique linguistic norms. The study emphasizes the need for further research to explore the underlying factors that influence these linguistic characteristics and their implications for educational practices.

Off-task behavior refers to any action by a learner that is unrelated to the learning task, and it can have a negative effect on learning outcomes. Determining when a behavior is off task is challenging because these behaviors vary across different learning environments and goals. Off-task behavior in Minecraft might be more difficult to detect because of the open-ended nature of the game, which allows learners to explore the environment and complete learning tasks in various ways. This study aims to model off-task behavior of learners using the What-If Hypothetical Implementations using Minecraft (WHIMC). Detector of off-task behavior was developed using features from the interaction logs of the learners in WHIMC. Initially, the detector was constructed using the basic feature set as the baseline, that includes the time-based features, frequency-based features, and sequence features. The feature set was further expanded to include exploration features and personalized features, and the performance of the models using different sets of features were compared. This study found that the detector built with the addition of exploration features to the baseline feature set showed slightly higher performance compared to the detector built using the baseline feature set. Then, the detector built using the feature set that also included personalized features had better performance compared to the detector using the feature set with the exploration features. Some selected exploration and personalized features were also found to be more predictive of off-task behavior compared to some features in the baseline feature set.

This paper uses the Framework for Teaching (FFT) by Charlotte Danielson as a lens to examine intra-pandemic educational practices of instructors at a higher education institution in the Philippines. It highlights teaching practices that have shown resilience and persistence over the nearly three years of the pandemic, during which education shifted from in-person delivery to one entirely online. Data from faculty surveys and interviews obtained in 2020 and 2023 showed a persistent set of practices that addresses all dimensions of teaching. Implications for post-pandemic education are briefly discussed.

This paper presents a study into the well-being of students using the Experience Sampling Method (ESM). The study aims to explore the relationships between locations, activities, and social interactions with emotional states over time, the dynamic interrelations among different emotional states, and the impact of daily activities on the transitions and stability of students' emotional states. The study leverages the Ateneo Experience Sampling App (AESapp) to collect real-time data on students' emotional states, activities, and contexts. Data was collected from 104 college students over two weeks, with participants responding to daily prompts about their emotions and situational contexts. To address the research questions, the study employed data science tools and methods. Findings indicate that leisure activities and social interactions with friends and significant others enhance positive emotions like happiness and engagement. In contrast, interactions with parents and classmates can increase negative emotions such as anger and sadness. The study also highlights the emotional stability provided by structured activities like schoolwork and leisure.

Researchers have long studied how novice programmers interpret compiler error messages during debugging. This study investigates the link between personalities and visual attention patterns. We measured traits using the Big Five Personality Test (John and Soto, 2017) and eye-tracking data from 63 participants at two Philippine universities. They located bugs in five programs with syntax errors, each 15 to 35 lines long, using constructs from the first 6 to 8 weeks of a programming course. Each program had one syntax error, either literal or non-literal. Participants viewed images of the programs and error messages, marking errors with a custom viewer. We found that students with high agreeableness and conscientiousness showed minimal attention to compiler error messages and error lines, respectively. The lack of correlation between these traits and performance scores makes it uncertain if these students with high agreeableness and high conscientiousness are also high performers. This study suggests educators might develop strategies potentially leveraging agreeableness and conscientiousness, such as collaborative learning. Future work will investigate run time errors, analyze patterns, and create strategies to help novices address them effectively.

Learning debugging is crucial for novice programmers, and as compiler error messages play a vital role in this process, exploring how novice programmers read and interpret these messages has become a focal point for researchers in computer science education. Understanding how novice programmers interpret compiler error messages is essential, as debugging skills are fundamental for their development. In line with this, our prior works investigated how student programmers process syntax errors embedded in Java and C++ programs and the relationship between novice programmers' personalities and their visual attention patterns using fixation-based metrics. Our previous studies were limited in that they did not capture the dynamics of the participants' eye movements. As our next step, in this study, we present saccade- based metrics that we used to gain insights into the problem-solving strategies employed by novice programmers. We found that high and low performing participants demonstrate similar strategies for scanning through code and detecting errors. Furthermore, high performing participants demonstrate longer average saccade lengths, indicative of purposeful exploration and the gathering of more information in each eye movement. Additionally, our findings indicate that high performing participants exhibit a lower average regression ratio, suggesting a greater ability to maintain focus and comprehension throughout problem-solving tasks. In future work, integrating contextual factors such as task complexity, familiarity with programming languages and individual learning styles into the analysis of saccade-based metrics can help identify situational factors shaping problem-solving strategies.

An escape room is a game in which a player or team of players is locked in a room or series of rooms. To exit the room successfully, they must solve puzzles or search for clues within a set amount of time. While commercial escape rooms are typically designed for entertainment, an escape room format can be used as an educational experience as well. A well-designed escape room can heighten engagement, provide immediate feedback, and help practice and cooperation. This paper describes the design and implementation of an educational escape rooms class at a major university in the Philippines. It describes the class's goals and objectives, and the major elements of an escape room's design. The class was offered during the second semester (January to May) of 2024 and the summer session (June to July) of 2024. The paper discusses two of the rooms that were designed by the members of the class, and some feedback from the games' alpha testers.

We present findings from a preliminary experience sampling study exploring the association between negative emotions (fear and sadness) and student day-to-day activities and circumstances including online use, location, and companions. Experience sampling is a data collection method in which individuals are asked for self-reports at random times of their waking hours. It is best used when data is episodic or experiential in nature. To this end, we created the Ateneo Experience Sampling App (AESApp), a mobile-based application that collects data about levels of student happiness, engagement, fear, sadness, and anger, as well as contextual information such as who they are with, what they are doing, and where they are. We found that students who reported not being online at the time they were prompted tended to report low levels of these emotions. Similarly, students who reported being with companions reported low levels of fear and sadness. In contrast, those who reported moderate to high levels of fear or sadness tended to be alone. Although the implications are interesting, they are suggestive rather than conclusive because of the small sample size. Moving forward, the research team needs to find ways to increase response rate.

This PDF file contains the front matter associated with ICCE Proceedings including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

We use CausalImpact analysis to compare student online activity during the COVID-19 pandemic, when all classes were online, and post-pandemic, when classes were offered in a mix of modes. Student activity was operationalized as activity logs from the Canvas Learning Management System (LMS). When compared with student activity in pandemic fully online classes, we found that, contrary to our hypotheses, student activity in post-pandemic fully online classes decreased while activity in post- pandemic fully onsite classes increased. We attribute the decrease in participation in fully online classes to factors such as Zoom fatigue and feelings of loneliness and prolonged isolation. The increase in student online activity in fully onsite classes might be explained by students’ general preference for face-to-face interactions. They may have felt more connected to teachers and peers, leading to greater productivity overall. The discourse about the transition from online learning brought on by the pandemic is dominated by survey research. By examining student online activity in an LMS, this paper contributes an analysis of empirical data that supports the findings of prior studies about student perceptions of the online learning experience and their adjustments to the next normal.

This paper examines the factors that affect the sustainable use of Minecraft-based lesson plans. We focus specifically on teachers who received training on using What-If Hypothetical Implementations in Minecraft (WHIMC), a set of Minecraft worlds designed to teach astronomy, geosciences, and ecology. We commissioned a group of teachers to develop lesson plans using at least one of the WHIMC worlds and pilot their implementation in their classes. Another group of teachers received training on developing learning modules with WHIMC but had the freedom to choose when and how to implement their lesson plans during the school year. The teachers cited logistical impediments, scheduling impediments, lack of technical resources, lack of curricular alignment, changes to teaching modalities, limited time for practice, and anxieties about classroom management as barriers to sustainable use of WHIMC. They suggested the training of additional teachers to create a community of practice whose members can collaborate and support each other's use of WHIMC for STEM education.

In this paper, we replicated the methods and findings of a study on successful completion of massive open online courses (MOOCs) in the context of online learning in a university in Metro Manila, Philippines. Specifically, we examine whether discussion forum behaviors associated with completion in MOOCs also resulted in better outcomes in university online learning courses. To this end, we collected logs from the university’s learning management system. The Mann-Whitney U test was used to compare the average scores of those who conformed to these behaviors and those who did not. Pearson’s r correlation was then used to determine if a significant relationship exists between each of the measured behaviors and the average scores of the students for each course. The same analyses were then performed for each of the five schools in the same university. The study failed to replicate the results of the MOOC study in all cases. The difference in means was not far apart for all rules. This could be attributed to the difference in pacing and demographic between universities and MOOCs. Despite these, the study still demonstrates that techniques used to study MOOCs can be used to study the behaviors and success indicators of students.

We determine the relationship between student STEM interest and four re- engagement metrics within a set of Minecraft worlds: number of concurrent players playing outside of class hours, number of observations made, number of worlds visited, and number of science tools used. With the exception of number of observations made, there were no significant relationships found between STEM interest and these re- engagement metrics. Therefore, the data so far does not provide much evidence that these behaviors are indicative of interest in STEM. Ways forward include later administration of the STEM interest questionnaire, hypothesizing other in-game behaviors, and identifying a more sensitive STEM interest instrument.

The difference in the visual attention of subjects while performing a debugging task can be measured using fixation count and fixation duration metrics. Thus, this paper investigated the visual attention patterns of high and low performing students engaged in a defect-finding task on multiple programs using these metrics. We performed statistical tests on the proportional fixation durations and fixation counts on the error lines and the compiler error messages to determine the difference in the visual attention patterns between the groups. The results of the statistical analysis revealed a significant difference between the high and low performing students across all programs. This implies that high performing students were associated with significantly higher visual attention on the error lines of the programs than the low performing students. However, the analysis of the proportional fixation duration and fixation count on the compiler error messages revealed no significant difference between the groups. The results suggest that both groups showed similar visual attention to the compiler error messages. The findings of this study provide insights into the visual attention patterns of student programmers in processing compiler error messages. High and low performing students could be distinguished based on their visual attention patterns on the error lines but not on the compiler error messages. Further, high performing students prefer a more analytical processing approach and pay attention to relevant code elements in debugging to correctly identify the errors while low performing students choose a more holistic approach.

For People and Planet: An SDG Adventure refers to a freely available Android-based narrative adventure game and teacher resource pack that helps learners see the United Nations Sustainable Development Goals (SDGs) in their day-to-day lives. In this paper, we describe the results of an evaluation of both the game and the resource pack by eight (8) middle school teachers. After playing the game and reading the resource pack, teachers gave their feedback about what they liked best and least about the materials, how they could use these resources for their classes, and how these resources could be improved further. Overall, teachers’ feedback was positive. They complemented the game’s visuals and sound design and appreciated the game’s contextualization. They affirmed the relevance of the game’s contents to their lessons and the usefulness of the teacher resource pack as it provided them with notes, additional activities, and sample assessments. They gave some useful suggestions such as the need for more visual cues with in the game and tutorials for the mini-games, and glossary of terms for the teacher resource pack. The game and resource pack underwent some revision following the feedback of the teachers. Performing the user test was essential to ensuring the quality of the game and the re source pack, and to increase the probability that the game will actually be used in schools.

We investigated the affective states (both individual and shared emotions) of students using a collaborative and educational game for English called Ibigkas! Our goal was two-fold: (1) To determine the incidence and persistence of affective states exhibited by the students when working individually and in groups, and (2) to adapt the Baker Rodrigo Ocumpaugh Monitoring Protocol for collaborative learning situations. Our findings for this study are as follows: (1) in single-player mode, students exhibited greater engaged concentration, pride, and frustration and less excitement, delight, and confusion compared to the multiplayer mode; (2) that individual emotions can be distinct from group emotions; (3) that negative emotions like frustration and blame/guilt were only felt at the individual level and were not observed as shared by all the members of the group; (4) affective states tended to persist more within an individualized game setting compared to the collaborative game setting where there was a greater number of opportunities to experience a wider range of emotions, hence the low chance of persistence; (5) students within an individualized setting spent more time solving the game rounds, had fewer incorrect answers, even as they experienced more frustration, and finally, (6) students within a collaborative setting had fewer errors when they had a higher incidence of excitement and had more errors when they appeared to be concentrating due to the presence of the “gaming the system” behavior.

Despite the call to develop culturally-aware educational technologies, very few studies were conducted in the Philippines. In order to contribute to this body of literature, this study has been conceived. This paper intends to model the “stag-and-hare” hunt behavior of students in the light of cultural orientation of the participants. It will use the interaction data that will be gathered through Ibigkas! Math – a mobile-supported collaborative learning application. Based on the developed model, the mobile application will be revised to make it more adaptive to students’ academic needs. The proposed methodology and future works are discussed.

This paper presents the testing and development of Learning Likha, an English language-based digital game for Filipino learners from 9- to 12-years old. The game focuses on the literacy skill of noting explicit details while incidentally learning about Filipino culture. In an in-vivo pilot test, we measured student comprehension and engagement. We found that the students who performed better and had greater confidence enjoyed using the software but were less engaged than those who performed more poorly.

English proficiency is vital in today’s global employment market. Digital games have been shown to help improve learners’ language competencies. However, it is sometimes difficult for teachers to maximize digital games as educational resources. In this paper, we discuss the development of a teacher’s guide as a companion to the digital games Ibigkas! and Learning Likha. Both games are intended to help improve the English proficiency of Filipino learners from 9 to 12 years old.

We discuss a field study in which 30 public school students from grades 4, 5, and 6 play Learning Likha, a mobile-based game for practicing English comprehension. Using self-report questionnaires, a comprehension test, BROMP observations, and game interaction logs, we assessed the extent to which students understood the game’s contents and enjoyed playing the game. We also tried to determine any relationships between student achievement, affect, and behavior. Self-reported feedback about the game was positive, with students reporting interest, enjoyment, and sufficient challenge. Students across all grade levels exhibited engaged concentration and on-task activity while playing the game. However, post-test comprehension scores were low, especially for the younger participants. On-task conversation and confusion were negatively correlated with achievement. Additionally, on-task behavior and engaged concentration were positively correlated with number of interface taps.

Incubation Effect (IE) refers to the phenomenon where one gets stuck in a problem-solving activity, decides to take a break, and afterwards revisits the unsolved problem and eventually solves it. While studies on IE were all limited to traditional classroom activities, this research aimed to continue the study of IE in the context of a computer-based learning environment and find features that would predict the incidence of revisiting an unsolved problem and its positive outcome. A prior IE model was developed using a logistic regression but the hand-crafted features used were from aggregated data and do not reflect specific characteristics of students’ actions. Further analysis was conducted in this study and used a deep learning technique which significantly improved the performance of the IE model. In order to interpret the learned features of the neural network, a combination of dimension reduction, visualization technique, and clustering were used. It was found that the coarse-grained features are consistent with the fine-grained features but action level features were also discovered which provided more evidence that there was an improvement on how students tried to solve the problem after incubation.

We present Drug Defense, a mobile tower defense game designed to prevent alcohol abuse. The game makes use of the Cognitive Behavioral Game Design (CBGD) methodology to encourage the retention of knowledge about the consequences of excessive alcohol use. The researchers compared used pretest and posttest to determine the game aided in greater retention. The researchers also assessed the playability of the game was also evaluated using a questionnaire adapted from the Heuristics to Evaluate the Playability (HEP) of Games. Data analysis showed that the players had significantly increased knowledge on alcohol and its use. Players also enjoyed the game’s narrative and the need to strategize.

We investigate the Incubation Effect (IE), a phenomenon by which a momentary break facilitates the generation of a solution to a problem, and its relationship with both achievement and affect of middle school students playing Physics Playground. Statistical data reports no significant improvement in the overall performance when breaks are done. Also, the success rate of solving problems after taking a break has no significant difference with the success rate of attempts without breaks. This could be attributed to the fact that the activity done during breaks is very similar to the problem-solving task, but further investigation needs to be done for validation. The results may say IE has not improved the in-game achievement of students, however, majority of IE occurrences resulted to success. This is evidence to support the positive effect of incubation. Also, a significant positive correlation was found between IE incidence and frustration.

A theory of cognition called embodied cognition believes that the development of thinking skills is distributed among mind, senses and the environment. Research into this field has resulted into the development of applications in different areas including Mathematics. This paper reports one part of a larger series of studies on the design and implementation of embodied cognition of Mathematics educational systems. We describe the migration and evaluation of a game called "Estimate It", a wearables-based game for teaching measurement estimation and geometry. Experts were invited to evaluate the game, for which a generally positive rating was acquired. The game's collaborative nature, its hands-on way of teaching estimation, and the incorporation of technology were seen as promising points. Infrastructure readiness, classroom control and adjustment to the new technology were areas of concern.

We investigate the extent to which Augmented Reality can contribute to effectiveness and enjoyment in the context of history-game-based learning. This paper presents a series of usability tests of a mobile Augmented Reality game application for learning Philippine history, Igpaw: Intramuros, with representatives of the game’s target audience. These tests discovered issues that compromised player enjoyment, including fatigue during gameplay, hurdles in learning AR-specific game mechanics, game repetitiveness, and outdoor safety concerns, in addition to minor technical issues. Nevertheless, the tests show the game’s high effectivity in teaching Philippine history.

We built logistic regression models to identify facial action units that are associated with affective states of Filipino students using Physics Playground, an educational game for Physics. We found that facial action units AU1 (Inner Brow Raiser), AU5 (Upper Lid Raiser) and AU6 (Cheek Raiser) are significantly associated with engaged concentration, AU20 (Lip Stretcher) with Frustration, AU12 (Lip Corner Puller) with Delight and AU6 with Happiness. We discuss features in the models and future work.

This paper continues prior work conducted on the analysis of moments of student learning in Physics Playground, a learning environment for qualitative physics. The study analyzed data from 60 tenth-grade students who used Physics Playground for 90 minutes. We detected spikes of student learning, or “eureka” moments, while solving physics problem. We then related these moments of insight to affective states labeled according to the BROMP protocol. Our hypothesis was that students would be confused before eureka moments, and experience delight afterwards. Contrary to this hypothesis, we found that eureka moments and the periods surrounding them were associated with a decrease in all affective states. No significant differences were found in comparing the affective profiles of students who experienced eureka and those who did not.

This paper investigates the phenomenon of frustration when taken alone and when part of other affective sequences. The study attempted to determine the incidence of frustration and sequences involving frustration and their relationship with student achievement. 60 high school students from a university in the Philippines were asked to use Physics Playground for 120 minutes. Human observers recorded student cognitive affective states following BROMP while the game itself logged student activity. Frustration was found to have the second highest incidence from among the other affective states. Frustration, as well as sequences involving frustration, was found to be negatively correlated to student achievement occurring more than chance.

This study tests the common wisdom that persistence leads to academic success. We explore indicators or markers of persistence exhibited by 60 students from Baguio City, Philippines as they played a game-based learning environment called Physics Playground. The study attempted to determine the extent to which the markers of persistence identified by Shute et al. (2013) – specifically time spent, number of level restarts, and number of level revisits – were related with achievement. When clustered the data into two, according to these features, the clusters only differed significantly in terms of time spent and number of restarts. Number of revisits was not significantly different. What was most interesting, though, was that gold and no-badge outcomes were significantly negatively correlated with time spent and significantly positively correlated with number of restarts. These findings imply Shute’s markers while possibly indicative of persistence may also be indicative of non-learning behaviors, most notably wheel spinning.

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 correlated with earning a gold badge (solving a problem with objects under par), positively correlated with earning a silver badge (solving a problem with objects over par), and positively correlated with stacking (drawing numerous small objects to reach the objective), a form of gaming the system.

The goal of this paper was to examine affect-related factors and its relationship with student learning while tutoring an agent called SimStudent. These affect-related factors are the negativity of student self-explanations, the incidence and persistence of student affective states. Secondary school students who were part of this study were asked to teach their SimStudents solve algebra equations and make them pass all the quizzes. Results revealed that students failed to learn which led us to investigate other factors that could have attributed to this failure. Although the non-negatively valenced self-explanations did not have significant relationships with the students’ learning gains, the self-explanations were helpful in terms of mathematical content and they generally exhibited positive attitudes when giving the self-explanations. Students also tended to perform better with higher levels of good confusion. Higher levels of boredom were associated with poorer learning. Boredom and confusion were the most persistent but both did not have significant relationships with student learning. Though the negative correlations of the negative self-explanations, incidence and persistence of boredom vis-à-vis learning were not significant, the findings imply that negativity is linked to students’ poor performance.

Augmented reality (AR) is an emerging technology for communicating learning contents. Several AR systems are designed for learning. However, studies that have investigated instructional strategies for applying AR are few. This investigation requires the implementation of prototypes that use state-of-the-art technology and sound learning theory. In this work, we implemented two prototypes for learning Filipino and German words by first developing a handheld AR platform. These prototypes demonstrate situated vocabulary learning. Using our AR system, students can learn words related to their current environment. We assessed the quality of these prototypes by conducting usability evaluations. For the theoretical grounding, we leveraged on multimedia learning theory to design the content. Through our handheld AR platform, we evaluated situated vocabulary learning by comparing our prototypes to a flash cards application. In the first evaluation, students scored significantly lower when using AR in an immediate post-test. However, this difference disappeared after taking into account the variability in usability scores via analysis of covariance. Taking account usability is fairer when comparing an emerging technology to traditional technology. Test scores were also not significantly different in a delayed post-test. In the second evaluation, although the post-test score and answering time of students did not differ, our results showed that they feel more satisfied and can keep their attention better when using AR. For the first time, we demonstrated situated vocabulary learning by using AR. Moreover, our preliminary study confirms the intuition that students can achieve the same score using AR, but with benefits such as ease in maintaining attention and increased satisfaction.

Augmented reality (AR) is an enabling technology for presenting information in relation to real objects or real environments. AR is situated multimedia or information that is positioned in authentic physical contexts. In this paper, we discuss how we address issues in creating AR content for educational settings. From the learning theory perspective, we explain that AR is a logical extension of multimedia learning theory. From the development perspective, we demonstrate how AR content can be created through our in situ authoring tool and our platform for handheld AR.

This paper examines the factors that affect the sustainable use of Minecraft-based lesson plans. We focus specifically on teachers who received training on using What-If Hypothetical Implementations in Minecraft (WHIMC), a set of Minecraft worlds designed to teach astronomy, geosciences, and ecology. We commissioned a group of teachers to develop lesson plans using at least one of the WHIMC worlds and pilot their implementation in their classes. Another group of teachers received training on developing learning modules with WHIMC but had the freedom to choose when and how to implement their lesson plans during the school year. The teachers cited logistical impediments, scheduling impediments, lack of technical resources, lack of curricular alignment, changes to teaching modalities, limited time for practice, and anxieties about classroom management as barriers to sustainable use of WHIMC. They suggested the training of additional teachers to create a community of practice whose members can collaborate and support each other’s use of WHIMC for STEM education.

Between the different traditional learning tools and the rapid rise of technology and ease of access to them, students are presented with a multitude of avenues for learning. With so many resources available, students have to learn to be selective. By finding out what tools and services students use the most, this research aims to determine how students avoid information overload and getting lost in cyberspace. To do this, a survey was carried out at the Ateneo de Manila University in Manila, Philippines. Using a print questionnaire, 942 students were asked 145 questions about their media usage for learning and related topics. Analysis of the data included analysis of variance and comparing mean values by creating rankings of the different media services. It was aimed to find out what services are used the most, and to what extent. The results showed that students are more inclined to use online resources such as Google, online course material and literature, though there is still great appreciation for traditional learning media such as books and printed handouts from teachers. Filipino students seem to prefer self-learning, whether through traditional or non-traditional means, rather than learning through social media.

We study the affective states exhibited by students using an intelligent tutoring system for Scatterplots with and without an interactive software agent, Scooter the Tutor. Scooter the Tutor had been previously shown to lead to improved learning outcomes as compared to the same tutoring system without Scooter. We found that affective states and transitions between affective states were very similar among students in both conditions. With the exception of the "neutral state,” no affective state occurred significantly more in one condition over the other. Boredom, confusion, and engaged concentration persisted in both conditions, representing both "virtuous cycles” and "vicious cycles” that did not appear to differ by condition. These findings imply that—although Scooter is well liked by students and improves student learning outcomes relative to the original tutor—Scooter does not have a large effect on students' affective states or their dynamics.

In this study, we attempted to quantify indicators of novice programmer progress in the task of writing programs, and we evaluated the use of these indicators for identifying academically at-risk students. Over the course of nine weeks, students completed five different graded programming exercises in a computer lab. Using an instrumented version of BlueJ, an integrated development environment for Java, we collected novice compilations and explored the errors novices encountered, the locations of these errors, and the frequency with which novices compiled their programs. We identified which frequently encountered errors and which compilation behaviors were characteristic of at-risk students. Based on these findings, we developed linear regression models that allowed prediction of students' scores on a midterm exam. However, the models derived could not accurately predict the at-risk students. Although our goal of identifying at-risk students was not attained, we have gained insights regarding the compilation behavior of our students, which may help us identify students who are in need of intervention.

We study the relationships between affective states and sequences and learner achievement using sequential pattern mining techniques. We found, in accordance with prior research, that boredom is an undesirable state that is both persistent and detrimental to learning. We also found that confusion punctuated with periods of engaged concentration contributes to learning. However, confusion alone has a negative impact on student achievement, possibly indicating that students are stuck. These results shed light on past results finding inconsistent relationships between confusion and learning.

We attempt to automatically detect student frustration, at a coarse-grained level, using measures distilled from student behavior within a learning environment for introductory programming. We find that each student's average level of frustration across five lab exercises can be detected based on the number of pairs of consecutive compilations with the same edit location, the number of pairs of consecutive compilations with the same error, the average time between compilations and the total number of errors. Attempts to detect frustration at a finer grain-size, identifying individual students' fluctuations in frustration between labs, were less successful. These results indicate that it is possible to detect frustration at a coarse-grained level, solely from coarse-grained data about students' behavior within a learning environment.

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 IDE-related on-task conversation are associated with lower achievement. We find that a student's midterm score can be tractably predicted with simple measures such as the student's average number of errors, number of pairs of compilations in error, number pairs of compilations with the same error, pairs of compilations with the same edit location and pairs of compilations with the same error location. This creates the potential to respond to evidence that a student is at-risk for poor performance before they have even completed a programming assignment.