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1. Open-ended Modeling Problems and Engineering Identity

   Swenson, J.; Treadway, E.; Lape, S.; Casson, A. (June 2023, ASEE annual conference proceedings)

   Engineering identity is an integral determinant of academic success in engineering school, as it allows students to have an understanding of themselves in relation to what they study. Studies in engineering and other STEM disciplines have shown a positive correlation between identity and retention. Previous studies by Carlone and Johnson, Hazari, and Godwin have examined the following facets of a STEM or engineering identity: performance, competence, recognition and interest. While many current papers examine how culture and social interactions may influence identity, this paper examines how doing engineering coursework can uncover or influence a student’s engineering identity. This comparative case study examines how two students’ experiences solving an Open-ended Modeling Problem (OEMP) in their statics class may have contributed to their engineering identities. Cristina and Dylan, our two cases, both recalled how they solved a problem about a hands-free crutch device in an interview at the end of the semester. None of the questions were explicitly about identity. The interviews indicate that both students were interested in solving these problems and recognized themselves as being capable of solving the problem. In the case of Cristina, the problem helped her build confidence, both through her understanding of the material and her problem solving abilities. Our results also saw both students discussing how the disciplinary authenticity made them ‘feel like an engineer.’ Implications of this work include a deeper understanding of how day-to-day problem solving within courses can influence engineering identity and may aid in understanding how certain activities and scaffolding can influence engineering identity. This is important as students who have strong engineering identities are more likely to stay in engineering, become competent engineers, and find success in their respective fields. This research can inform educators on the importance of assigning novel, ill-defined problems that require students to apply their critical thinking skills and logic skills in real world situations. 

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2. An Open-Source BinaryGame for Learning Reverse Engineering

   Gourdine, D'Angelo; Matthews, Suzanne J. (April 2023, Journal of computing sciences in colleges)

   This paper introduces an open-source BinaryGame that assists students learning reverse engineering. The game consists of ten levels that increase in difficulty, help pages on GDB, and supports three flavors of assembly language. Work on the BinaryGame is ongoing; for our initial study, we used the BinaryGame to introduce students in a computer systems \& organization course to Arm assembly. These students had prior knowledge of x64 assembly, but no prior knowledge of Arm assembly; our goal was to boost our students' confidence in learning unfamiliar assembly languages. Our results suggest that the BinaryGame increased student confidence in their a.) general reverse engineering abilities; b.) ability to reverse engineer programs in an unfamiliar assembly language, and c.) ability to reverse programs in Arm assembly. We believe that the BinaryGame can help students build their reverse engineering skillset. 

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3. Learner Modeling Interpretability and Explainability in Intelligent Adaptive Systems

   https://doi.org/10.1007/978-3-031-58363-6_7  

   Zapata-Rivera, Diego; Arslan, Burcu (January 2024, Springer Nature Switzerland)

   Learner models are used to support the implementation of personalization features in Adaptive Instructional Systems (AISs; e.g., adaptive sequencing of activities, adaptive feedback), which are important aspects of Intelligent Adaptive Systems. With the increased computational power, more advanced methodologies, and more available data, learner models include a variety of Artificial Intelligence techniques. These techniques have different levels of complexity, which influence interpretability and explainability of learner models. Interpretable and explainable learner models can facilitate appropriate use of the learner modeling information in AISs, their adoption, and scalability. This chapter elaborates on the definitions of interpretability and explainability, describes interpretability and explainability levels of different models, elaborates on the levels of explainability to produce needed information for teachers and learners, and discusses implications and future work in this area. 

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4. How do students perceive their own and their peers' progress in e-learning?

   https://doi.org/10.1108/IJILT-05-2020-0073  

   Somyürek, Sibel; Brusilovsky, Peter; Çebi, Ayça; Akhüseyinoğlu, Kamil; Güyer, Tolga (November 2020, The International Journal of Information and Learning Technology)

   null (Ed.)

   Purpose Interest is currently growing in open social learner modeling (OSLM), which means making peer models and a learner's own model visible to encourage users in e-learning. The purpose of this study is to examine students' views about the OSLM in an e-learning system. Design/methodology/approach This case study was conducted with 40 undergraduate students enrolled in advanced programming and database management system courses. A Likert-type questionnaire and open-ended questions were used to obtain the students' views. System usage data were also analyzed to ensure the richness and diversity of the overall data set. Findings The quantitative data of the students' views were analyzed with descriptive statistics; the results are presented as graphics. The qualitative data of the students' views were examined by content analysis to derive themes. These themes are organized into four subtopics: the students' positive views, their negative views, their improvement suggestions and their preferences about using similar OSLM visualizations in other e-learning systems. The students' subjective views are discussed in the context of their recorded interactions with the system. Research limitations/implications Competition due to seeing peer models was considered by participants both as positive and negative features of the learning system. So, this study revealed that, the ways to combine peer learner models to e-learning systems that promote positive competition without resulting social pressure, still need to be explored. Practical implications By combining open learner models with open peer models, OSLM enhances the learning process in three different ways: it supports self-regulation, encourages competition and empowers self-evaluation. To take advantage of these positive contributions, practitioners should consider enhancing e-learning systems with both own learner and peer model features. Originality/value Despite increasing interest in OSLM studies, several limitations and problems must be addressed such as sparsity of data and lack of study of different contexts and cultures. To date, no published study in this area exists in Turkey. The purpose of this study is to fill this gap by examining OSLM features in an e-learning system from the perspectives of Turkish students by using both their system interaction data and their subjective views. 

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5. Developing an Introductory Computer Science Course for Pre-service Teachers

   Adler, Rachel F; Beck, Kristan (January 2020, Journal of technology and teacher education)

   Computational thinking (CT) involves breaking a problem into smaller components and solving it using algorithmic thinking and abstraction. CT is no longer exclusively for computer scientists but for everyone. While CT does not necessarily require programming, learning programming to enhance CT skills at a young age can help shape the next generation of children with knowledge that can help them succeed in our technological world. In order to produce teachers who are able to incorporate programming and CT into their future classrooms, we created an introductory Computer Science course (CS0) targeting future K-8 STEM teachers yet open to any student to enroll and learn computer science. We used a mixed-methods approach, examining both quantitative and qualitative data based on self-reported surveys, classroom artifacts, and focus groups from four semesters of data. We found that after taking the course, students’ self-efficacy in CT increased and while education students initially had lower confidence in their computing abilities than computer science students in the course, by the end of the semester there were no differences in their perceived and actual coding abilities when compared with computer science students. Furthermore, education students had many ideas on how to incorporate similar projects into their own future classrooms. 

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