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1. Autonomy and Types of Informational Text Presentations in Game-Based Learning Environments

   Denver, Daryn ; Azevedo, Roger ( January 2019 , International Conference on Artificial Intelligence in Education)

   Abstract. Game-based learning environments (GBLEs) are being increasingly utilized in education and training to enhance and encourage engagement and learning. This study investigated how students, who were afforded varying levels of autonomy, interacted with two types of informational text presentations (e.g., non-player character (NPC) instances, traditional informational text) while problem solving with CRYSTAL ISLAND (CI), a GBLE, and their effect on overall learning by examining eye-tracking and performance data. Ninety undergraduate students were randomly assigned to two conditions, full and partial agency, which varied in the amount of autonomy students were granted to explore CI and interactive game elements (i.e., reading informational text, scanning food items). Within CI, informational text is presented in a traditional format, where there are large chunks of text presented at a single time represented as books and research articles, as well as in the form of participant conversation with NPCs throughout the environment. Results indicated significantly greater proportional learning gain (PLG) for participants in the partial agency condition than in the full agency condition. Additionally, longer participant fixations on traditionally presented informational text positively predicted participant PLG. Fixation durations were significantly longer in the partial agency condition than the full agency condition. However, the combinationmore »of visual and verbal text represented by NPCs were not significant predictors of PLGs and do not differ across conditions.« less
2. Examining Gaze Behaviors and Metacognitive Judgments of Informational Text Within Game-Based Learning Environments

   Dever, Daryn ; Azevedo, Roger ( January 2019 , International Conference on Artificial Intelligence in Education)

   Abstract. Game-based learning environments (GBLEs) are often criticized for not offering adequate support for students when learning and problem solving within these environments. A key aspect of GBLEs is the verbal representation of information such as text. This study examined learners’ metacognitive judgments of informational text (e.g., books and articles) through eye gaze behaviors within CRYSTAL ISLAND (CI). Ninety-one undergraduate students interacted with game elements during problem-solving in CI, a GBLE focused on facilitating the development of self-regulated learning (SRL) skills and domain-specific knowledge in microbiology. The results suggest engaging with informational text along with other goal-directed actions (actions needed to achieve the end goal) are large components of time spent within CI. Our findings revealed goal-directed actions, specifically reading informational texts, were significant predictors of participants’ proportional learning gains (PLGs) after problem solving with CI. Additionally, we found significant differences in PLGs where participants who spent a greater time fixating and reengaging with goal- relevant text within the environment demonstrated greater proportional learning after problem solving in CI.
3. Using sequence mining to reveal the efficiency in scientific reasoning during STEM learning with a game-based learning environment

   Taub, M. ; Azevedo, R. ; Bradbury, A. ; Millar, G. ; Lester, J. ( January 2018 , Learning and instruction)

   The goal of this study was to assess how metacognitive monitoring and scientific reasoning impacted the efficiency of game completion during learning with Crystal Island, a game-based learning environment that fosters self-regulated learning and scientific reasoning by having participants solve the mystery of what illness impacted inhabitants of the island. We conducted sequential pattern mining and differential sequence mining on 64 undergraduate participants’ hypothesis testing behavior. Patterns were coded based on the relevancy of what items were being tested for, and the items themselves. Results revealed that participants who were more efficient at solving the mystery tested significantly fewer partially-relevant and irrelevant items than less efficient participants. Additionally, more efficient participants had fewer sequences of testing items overall, and significantly lower instance support values of the PartiallyRelevant--Relevant to Relevant--Relevant and PartiallyRelevant--PartiallyRelevant to Relevant--Partially Relevant sequences compared to less efficient participants. These findings have implications for designing adaptive GBLEs that scaffold participants based on in-game behaviors.
4. Using Sequence Mining to Analyze Metacognitive Monitoring and Scientific Inquiry based on Levels of Efficiency and Emotions during Game-Based Learning

   Taub, M. ; Azevedo, R. ( December 2018 , Journal of educational data mining)

   Self-regulated learning conducted through metacognitive monitoring and scientific inquiry can be influenced by many factors, such as emotions and motivation, and are necessary skills needed to engage in efficient hypothesis testing during game-based learning. Although many studies have investigated metacognitive monitoring and scientific inquiry skills during game-based learning, few studies have investigated how the sequence of behaviors involved during hypothesis testing with game-based learning differ based on both efficiency level and emotions during gameplay. For this study, we analyzed 59 undergraduate students’ (59% female) metacognitive monitoring and hypothesis testing behavior during learning and gameplay with CRYSTAL ISLAND, a game-based learning environment that teaches students about microbiology. Specifically, we used sequential pattern mining and differential sequence mining to determine if there were sequences of hypothesis testing behaviors and to determine if the frequencies of occurrence of these sequences differed between high or low levels of efficiency at finishing the game and high or low levels of facial expressions of emotions during gameplay. Results revealed that students with low levels of efficiency and high levels of facial expressions of emotions had the most sequences of testing behaviors overall, specifically engaging in more sequences that were indicative of less strategic hypothesis testing behaviormore »than the other students, where students who were more efficient with both levels of emotions demonstrated strategic testing behavior. These results have implications for the strengths of using educational data mining techniques for determining the processes underlying patterns of engaging in self-regulated learning conducted through hypothesis testing as they unfold over time; for training students on how to engage in the self-regulation, scientific inquiry, and emotion regulation processes that can result in efficient gameplay; and for developing adaptive game-based learning environments that foster effective and efficient self-regulation and scientific inquiry during learning.« less
5. Long-Term Outcomes of RET Programs on Female and Minority Student High School Graduation Rates and Undergraduate STEM Major Rates (Fundamental)

   Nichol, C. ; Crawford, C. A. ; Barr, C. ; Cerda, I. ( January 2021 , ASEE Annual Conference proceedings)

   Research Experience for Teachers (RET) programs are National Science Foundation (NSF) funded programs designed to provide K- 12 Science, Technology, Engineering, and Mathematics (STEM) teachers with immersive, hands-on research experiences at Universities around the country. The NSF RET in nanotechnology encourages teachers to translate cutting-edge research into culturally relevant Project-Based Learning (PjBL) and engineering curriculum. Traditionally, the evaluation of RET programs focuses on the growth and development of teacher self-efficacy, engineering content knowledge gains, or classroom implementation of developed curriculum materials. However, reported methods for evaluating the impact of RETs on their female, minority student populations' high school graduation and undergraduate STEM major rates are limited. This study's objective was to compare RET high school student graduation rates and undergraduate STEM major rates across gender, race, and ethnicity to a comparison sample to determine the RET program's long-term impact on students' likelihood of pursuing STEM careers. The approach of collecting and analyzing the Texas Education Research Center Database (EdRC) data is a novel methodology for assessing RET programs' effectiveness on students. The EdRC is a repository of K-12 student data from the Texas Education Agency (TEA) and Higher Education data from the Texas Higher Education Coordinating Board (THECB). This jointmore »database contains demographic, course registration, graduation, standardized testing, and college major, among others, for all students that attended a K-12 public school in Texas and any college in Texas, public or private. The RET program participants at Rice University (2010 – 2018) taught numerous students, a sample size of 11,240 students. A propensity score matching generated the student comparison group within the database. Students' school campus, gender, race/ethnic status, and English proficiency status were applied to produce a graduation comparison sample size of 11,240 students of Non-RET participants. Linking the TEA database to the THECB database resulted in college STEM participants and comparison sample sizes of 4,029 students. The project team conducted a logistic regression using RET status to predict high school graduation rates as a whole and by individual variables: gender, Asian American, Black, Caucasian, and Latinx students. All models were significant at p less than 0.05, with models in favor of students RET teachers. The project team conducted a logistic regression using RET status to predict student STEM undergraduate major rates as a whole and by individual variables: Gender, Asian American, Black, Caucasian, and Latinx students. African American and Caucasian models were significant at p less than 0.05; Gender, Asian American, and Latinx models were marginally significant (0.05 less than p greater than 0.1), where RET students had higher STEM major rates than matched controls. The findings demonstrate that RET programs have a long-term positive impact on the students' high school graduation rates and undergraduate STEM major rates. As teachers who participate in the RET programs are more likely to conduct courses using PjBL strategies and incorporate real-world engineering practices, female and minority students are more likely to benefit from these practices and seek careers utilizing these skills.« less