Contribution: This article applies science capital research to computing education in order to understand why students engage with a programme involving computing, and what they aspire to get out of their education. Background: Capital is a concept which has been used in educational research to study inequality, aspiration and achievement. Previous work has looked at capital in science education, but misses out on discipline-specific capital. This article applies science capital research to the field of computing education, providing insight into students’ views and dispositions of computing, their confidence and knowledge, and other factors which are important for understanding student engagement with the subject. Research Questions: How can science capital research be adapted to computing education? Further to this, what insights can be generated from such a methodology? Methodology: Inspired by the concept of science capital, a survey has been developed and tested among 29 bioinformatics students with a biology background. These students were selected since they recently switched to a programme involving computing, allowing them to reflect on their motivation, aspirations, and outcome expectations. Informed by the initial results, a follow-up interview was designed, and ten students participated. Findings: Science capital research proves useful for studying factors underlying participation in computing. Students in this study are driven by career opportunities, as well as positive beliefs and values when it comes to computing, while perceiving barriers such as low levels of computing confidence, and a gap between their skills and future careers. In addition, gender differences among survey results were observed $(p,,=$ 0.002).
{"title":"From Science to Computing: A Study of Capital Among Bioinformatics Students","authors":"Thom Kunkeler;Aletta Nylén","doi":"10.1109/TE.2023.3347096","DOIUrl":"10.1109/TE.2023.3347096","url":null,"abstract":"Contribution: This article applies science capital research to computing education in order to understand why students engage with a programme involving computing, and what they aspire to get out of their education. Background: Capital is a concept which has been used in educational research to study inequality, aspiration and achievement. Previous work has looked at capital in science education, but misses out on discipline-specific capital. This article applies science capital research to the field of computing education, providing insight into students’ views and dispositions of computing, their confidence and knowledge, and other factors which are important for understanding student engagement with the subject. Research Questions: How can science capital research be adapted to computing education? Further to this, what insights can be generated from such a methodology? Methodology: Inspired by the concept of science capital, a survey has been developed and tested among 29 bioinformatics students with a biology background. These students were selected since they recently switched to a programme involving computing, allowing them to reflect on their motivation, aspirations, and outcome expectations. Informed by the initial results, a follow-up interview was designed, and ten students participated. Findings: Science capital research proves useful for studying factors underlying participation in computing. Students in this study are driven by career opportunities, as well as positive beliefs and values when it comes to computing, while perceiving barriers such as low levels of computing confidence, and a gap between their skills and future careers. In addition, gender differences among survey results were observed \u0000<inline-formula> <tex-math>$(p,,=$ </tex-math></inline-formula>\u0000 0.002).","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139950963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: This longitudinal study modeled student leadership growth in a course sequence supporting long-term, large-scale, multidisciplinary projects embedded in faculty research. Students (half from computer science, computational media, electrical engineering, and computer engineering) participated for 1–4 semesters. Background: Project- based learning (PBL) is used widely in higher education. It is used in industry for leadership development, but leadership development in project-based learning (PBL) has not been explored in higher education. A preliminary analysis implied leadership growth through the third semester of participation, but the design did not control for attrition. Research Questions: At the student level, how do leadership role ratings change over multiple semesters of participation? Do first (and second) semester ratings differ by number of semesters students eventually participate? Methodology: The study involved two peer evaluation questions on 1) the degree to which students coordinated the team’s work and 2) served as technical/content area leaders. Analysis employed analysis of variance to examine attrition by initial ratings (N = 1045) and multilevel growth modeling to study change over time (N = 585). A strength of using peer evaluations is the large sample size, but a weakness is that the tool was developed for student assessment and not educational research. The study did not control for participation in leadership programs outside the course. Findings: On average, individual leadership role ratings increased each semester through the third semester of participation. Ratings of students who left the program after 1 or 2 semesters did not differ from ratings for those who participated longer.
{"title":"Leadership Growth Over Multiple Semesters in Project-Based Student Teams Embedded in Faculty Research (Vertically Integrated Projects)","authors":"Julia Sonnenberg-Klein;Edward J. Coyle","doi":"10.1109/TE.2023.3344314","DOIUrl":"10.1109/TE.2023.3344314","url":null,"abstract":"Contribution: This longitudinal study modeled student leadership growth in a course sequence supporting long-term, large-scale, multidisciplinary projects embedded in faculty research. Students (half from computer science, computational media, electrical engineering, and computer engineering) participated for 1–4 semesters. Background: Project- based learning (PBL) is used widely in higher education. It is used in industry for leadership development, but leadership development in project-based learning (PBL) has not been explored in higher education. A preliminary analysis implied leadership growth through the third semester of participation, but the design did not control for attrition. Research Questions: At the student level, how do leadership role ratings change over multiple semesters of participation? Do first (and second) semester ratings differ by number of semesters students eventually participate? Methodology: The study involved two peer evaluation questions on 1) the degree to which students coordinated the team’s work and 2) served as technical/content area leaders. Analysis employed analysis of variance to examine attrition by initial ratings (N = 1045) and multilevel growth modeling to study change over time (N = 585). A strength of using peer evaluations is the large sample size, but a weakness is that the tool was developed for student assessment and not educational research. The study did not control for participation in leadership programs outside the course. Findings: On average, individual leadership role ratings increased each semester through the third semester of participation. Ratings of students who left the program after 1 or 2 semesters did not differ from ratings for those who participated longer.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10388277","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139950993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Selina Marianna Shah, Catherine Elliott, Prema Nedungadi
{"title":"Square Pegs and Round Holes: Pedagogy for Autistic Students in Computing Education","authors":"Selina Marianna Shah, Catherine Elliott, Prema Nedungadi","doi":"10.1109/te.2023.3335395","DOIUrl":"https://doi.org/10.1109/te.2023.3335395","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139950920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sara Ricci;Simon Parker;Jan Jerabek;Yianna Danidou;Argyro Chatzopoulou;Remi Badonnel;Imre Lendak;Vladimir Janout
Demand for cybersecurity professionals from industry and institutions is high, driven by an increasing digitization of society and the growing range of potential targets for cyber attacks. However, despite this pressing need a significant shortfall in the number of cybersecurity experts remains and a discrepancy has emerged between the skills introduced through education and those required in professional settings. In this article, a political, economic, social, technological, legal, and environmental (PESTLE) analysis was utilized to explore the factors impacting cybersecurity education in Europe. The PESTLE analysis enabled the categorization of factors affecting cybersecurty education and skills and allowed for cybersecurity professionals to assess the relevance of the factors at a national-level and European-level. Utilizing the concept of modularity from social network analysis, the interconnectivity of factors was also considered. Finally, a European-level stakeholder survey was conducted to verify the findings. As a result of the above process, a lack of societal awareness of cybersecurity was identified as a major challenge to education, along with a lack of EU-level certification. It should be noted that significant differences between factors perceived as impacting cybersecurity education were found between countries suggesting a need for local solutions to the problem.
{"title":"Understanding Cybersecurity Education Gaps in Europe","authors":"Sara Ricci;Simon Parker;Jan Jerabek;Yianna Danidou;Argyro Chatzopoulou;Remi Badonnel;Imre Lendak;Vladimir Janout","doi":"10.1109/TE.2023.3340868","DOIUrl":"10.1109/TE.2023.3340868","url":null,"abstract":"Demand for cybersecurity professionals from industry and institutions is high, driven by an increasing digitization of society and the growing range of potential targets for cyber attacks. However, despite this pressing need a significant shortfall in the number of cybersecurity experts remains and a discrepancy has emerged between the skills introduced through education and those required in professional settings. In this article, a political, economic, social, technological, legal, and environmental (PESTLE) analysis was utilized to explore the factors impacting cybersecurity education in Europe. The PESTLE analysis enabled the categorization of factors affecting cybersecurty education and skills and allowed for cybersecurity professionals to assess the relevance of the factors at a national-level and European-level. Utilizing the concept of modularity from social network analysis, the interconnectivity of factors was also considered. Finally, a European-level stakeholder survey was conducted to verify the findings. As a result of the above process, a lack of societal awareness of cybersecurity was identified as a major challenge to education, along with a lack of EU-level certification. It should be noted that significant differences between factors perceived as impacting cybersecurity education were found between countries suggesting a need for local solutions to the problem.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139950992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: This work examines the impact of a unique precollege STEM education initiative during its two pilot years. The study contributes to the growing body of research by unpacking the needs of and the impact on an important stakeholder group (i.e., the teachers) in the engineering education ecosystem to help inform the future design and development of teacher professional learning models. Background: Efforts to provide precollege students with engineering or robotics-specific experiences are on the rise. These efforts are typically undertaken independently of one another. A first-of-its-kind collaboration between two precollege STEM initiatives aimed to break down existing silos between programs and offer a blended engineering and robotics curriculum targeting underserved schools. Research Questions: 1) How does a program designed to blend two existing engineering and robotics programs at the secondary school level impact teachers? and 2) What program elements are deemed valuable by participating teachers who are implementing a blended engineering and robotics program at the secondary school level? Methodology: Four focus groups were conducted with teachers ( ${n}$ = 16) over a period of two years. Data was analyzed using open coding and constant comparison methods. Findings: Four themes of growing confidence, exercising agency, responsive professional development, and support structures emerged across the four datasets. Collectively these themes capture pragmatic understandings of offering a new, blended precollege STEM program and advance an argument for the involvement of all stakeholders to support the teachers.
{"title":"Blended Implementation of Existing Precollege Engineering Programs: Teacher Perspectives of Program Impact","authors":"Medha Dalal;Assad Iqbal;Adam R. Carberry","doi":"10.1109/TE.2023.3338610","DOIUrl":"https://doi.org/10.1109/TE.2023.3338610","url":null,"abstract":"Contribution: This work examines the impact of a unique precollege STEM education initiative during its two pilot years. The study contributes to the growing body of research by unpacking the needs of and the impact on an important stakeholder group (i.e., the teachers) in the engineering education ecosystem to help inform the future design and development of teacher professional learning models. Background: Efforts to provide precollege students with engineering or robotics-specific experiences are on the rise. These efforts are typically undertaken independently of one another. A first-of-its-kind collaboration between two precollege STEM initiatives aimed to break down existing silos between programs and offer a blended engineering and robotics curriculum targeting underserved schools. Research Questions: 1) How does a program designed to blend two existing engineering and robotics programs at the secondary school level impact teachers? and 2) What program elements are deemed valuable by participating teachers who are implementing a blended engineering and robotics program at the secondary school level? Methodology: Four focus groups were conducted with teachers (\u0000<inline-formula> <tex-math>${n}$ </tex-math></inline-formula>\u0000 = 16) over a period of two years. Data was analyzed using open coding and constant comparison methods. Findings: Four themes of growing confidence, exercising agency, responsive professional development, and support structures emerged across the four datasets. Collectively these themes capture pragmatic understandings of offering a new, blended precollege STEM program and advance an argument for the involvement of all stakeholders to support the teachers.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10376265","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141245206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Isaac Dunmoye;Olanrewaju Olaogun;Nathaniel Hunsu;Dominik May;Robert Baffour
Contribution: The study examines the predictive and mediating significance of social and teaching presences on cognitive presence in a Community of Inquiry (CoI) mediated by a desktop virtual reality (VR). The findings of this study have implications for how to leverage VR learning environments to support meaningful collaborative engagement. Background: VR offers teaching and learning possibilities that can be leveraged to scale the engineering learning environment and enhance students’ learning experiences in ways that other instructional technologies used in engineering contexts cannot. However, VR must integrate and support social presence to enhance students’ learning experience. Because learning in VR is a recent phenomenon, there is need for more research on how to facilitate cognitive presence in VR environments. Research Questions: What is the predictive and mediating significance of social and teaching presence on the cognitive presence in a collaborative VR learning environment? Methodology: Participants in a CoI framework responded to a questionnaire after working collaboratively to perform land-surveying activities in a desktop VR platform. Path analysis of two models was conducted to examine the significance of teaching and social presence as predictors of cognitive presence. Findings: The results of this study revealed that both social presence and teaching presence were significant predictors of cognitive presence. The study also showed that social presence was a better predictor and mediator of cognitive presence than teaching presence. However, the teaching presence effect was sufficiently relevant to the two models examined.
{"title":"Examining the Predictive Relationships Between Presences of a Community of Inquiry in a Desktop Virtual Reality (VR) Learning Environment","authors":"Isaac Dunmoye;Olanrewaju Olaogun;Nathaniel Hunsu;Dominik May;Robert Baffour","doi":"10.1109/TE.2023.3340101","DOIUrl":"https://doi.org/10.1109/TE.2023.3340101","url":null,"abstract":"Contribution: The study examines the predictive and mediating significance of social and teaching presences on cognitive presence in a Community of Inquiry (CoI) mediated by a desktop virtual reality (VR). The findings of this study have implications for how to leverage VR learning environments to support meaningful collaborative engagement. Background: VR offers teaching and learning possibilities that can be leveraged to scale the engineering learning environment and enhance students’ learning experiences in ways that other instructional technologies used in engineering contexts cannot. However, VR must integrate and support social presence to enhance students’ learning experience. Because learning in VR is a recent phenomenon, there is need for more research on how to facilitate cognitive presence in VR environments. Research Questions: What is the predictive and mediating significance of social and teaching presence on the cognitive presence in a collaborative VR learning environment? Methodology: Participants in a CoI framework responded to a questionnaire after working collaboratively to perform land-surveying activities in a desktop VR platform. Path analysis of two models was conducted to examine the significance of teaching and social presence as predictors of cognitive presence. Findings: The results of this study revealed that both social presence and teaching presence were significant predictors of cognitive presence. The study also showed that social presence was a better predictor and mediator of cognitive presence than teaching presence. However, the teaching presence effect was sufficiently relevant to the two models examined.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141245234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jin Wei-Kocsis;Moein Sabounchi;Gihan J. Mendis;Praveen Fernando;Baijian Yang;Tonglin Zhang
Contribution: A novel proactive and collaborative learning paradigm was proposed to engage learners with different backgrounds and enable effective retention and transfer of the multidisciplinary artificial intelligence (AI)-cybersecurity knowledge. Specifically, the proposed learning paradigm contains: 1) an immersive learning environment to motivate the students for exploring AI/ machine learning (ML) development in the context of real-world cybersecurity scenarios by constructing learning models with tangible objects and 2) a proactive education paradigm designed with the use of collaborative learning activities based on game-based learning and social constructivism. Background: Increasing evidence shows that AI techniques can be manipulated, evaded, and misled, which can result in new and profound security implications. There is an education and training gap to foster a qualified cyber-workforce that understands the usefulness, limitations, and best practices of AI technologies in the cybersecurity domain. Efforts have been made to incorporate a comprehensive curriculum to meet the demand. There still remain essential challenges for effectively educating students on the interaction of AI and cybersecurity. Intended Outcomes: A novel proactive and collaborative learning paradigm is proposed to educate and train a qualified cyber-workforce in this new era where security breaches, privacy violations, and AI have become commonplace. Application Design: The development of this learning paradigm is grounded in the pedagogical approaches of technology-mediated learning and social constructivism. Findings: Although the research work is still ongoing, the prototype learning paradigm has shown encouraging results in promoting the learners’ engagement in applied AI learning.
{"title":"Cybersecurity Education in the Age of Artificial Intelligence: A Novel Proactive and Collaborative Learning Paradigm","authors":"Jin Wei-Kocsis;Moein Sabounchi;Gihan J. Mendis;Praveen Fernando;Baijian Yang;Tonglin Zhang","doi":"10.1109/TE.2023.3337337","DOIUrl":"https://doi.org/10.1109/TE.2023.3337337","url":null,"abstract":"Contribution: A novel proactive and collaborative learning paradigm was proposed to engage learners with different backgrounds and enable effective retention and transfer of the multidisciplinary artificial intelligence (AI)-cybersecurity knowledge. Specifically, the proposed learning paradigm contains: 1) an immersive learning environment to motivate the students for exploring AI/ machine learning (ML) development in the context of real-world cybersecurity scenarios by constructing learning models with tangible objects and 2) a proactive education paradigm designed with the use of collaborative learning activities based on game-based learning and social constructivism. Background: Increasing evidence shows that AI techniques can be manipulated, evaded, and misled, which can result in new and profound security implications. There is an education and training gap to foster a qualified cyber-workforce that understands the usefulness, limitations, and best practices of AI technologies in the cybersecurity domain. Efforts have been made to incorporate a comprehensive curriculum to meet the demand. There still remain essential challenges for effectively educating students on the interaction of AI and cybersecurity. Intended Outcomes: A novel proactive and collaborative learning paradigm is proposed to educate and train a qualified cyber-workforce in this new era where security breaches, privacy violations, and AI have become commonplace. Application Design: The development of this learning paradigm is grounded in the pedagogical approaches of technology-mediated learning and social constructivism. Findings: Although the research work is still ongoing, the prototype learning paradigm has shown encouraging results in promoting the learners’ engagement in applied AI learning.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141245205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: A novel undergraduate course design at the intersection of software engineering (SE) and machine learning (ML) based on industry-reported challenges. Background: ML professionals report that building ML systems is different enough that we need new knowledge about how to infuse ML into software production. For instance, various experts need to be deeply involved with these SE projects, such as business analysts, data scientists, and statisticians. Intended outcomes: The creation of a table detailing and matching industry challenges with course learning objectives, course topics, and related activities. Application design: Course content was derived from interviewing industry professionals with related experience as well as surveying undergraduate SE students. The proposed course style is designed to emulate real-world ML-based SE. Findings: Industry-derived content for a pilot undergraduate course has been successfully crafted at the intersection of SE and ML.
贡献：基于行业报告的挑战，在软件工程（SE）和机器学习（ML）的交叉领域设计新颖的本科课程。背景：机器学习专业人士报告说，构建机器学习系统与以往不同，我们需要关于如何将机器学习融入软件生产的新知识。例如，各种专家需要深入参与这些 SE 项目，如业务分析师、数据科学家和统计学家。预期成果：创建一个表格，详细说明行业挑战并将其与课程学习目标、课程主题和相关活动相匹配。应用设计：课程内容来自于对具有相关经验的行业专业人士的访谈以及对本科 SE 学生的调查。建议的课程风格旨在模仿现实世界中基于 ML 的 SE。研究结果：在 SE 和 ML 的交叉点上，成功地为试点本科课程设计了源自行业的内容。
{"title":"Teaching Machine Learning as Part of Agile Software Engineering","authors":"Steve Chenoweth;Panagiotis K. Linos","doi":"10.1109/TE.2023.3337343","DOIUrl":"https://doi.org/10.1109/TE.2023.3337343","url":null,"abstract":"Contribution: A novel undergraduate course design at the intersection of software engineering (SE) and machine learning (ML) based on industry-reported challenges. Background: ML professionals report that building ML systems is different enough that we need new knowledge about how to infuse ML into software production. For instance, various experts need to be deeply involved with these SE projects, such as business analysts, data scientists, and statisticians. Intended outcomes: The creation of a table detailing and matching industry challenges with course learning objectives, course topics, and related activities. Application design: Course content was derived from interviewing industry professionals with related experience as well as surveying undergraduate SE students. The proposed course style is designed to emulate real-world ML-based SE. Findings: Industry-derived content for a pilot undergraduate course has been successfully crafted at the intersection of SE and ML.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141245138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: An AI model for speech emotion recognition (SER) in the educational domain to analyze the correlation between students’ emotions, discussed topics in teams, and academic performance.Background: Research suggests that positive emotions are associated with better academic performance. On the other hand, negative emotions have a detrimental impact on academic achievement. This highlights the importance of taking into account the emotional states of the students to promote a supportive learning environment and improve their motivation and engagement. This line of research allows the development of tools that allow educators to address students’ emotional needs and provide timely support and interventions. Intended Outcome: This work analyzes students’ conversations and their expressed emotions as they work on class activities in teams and investigates if their conversations are course-related or not by applying topic extraction to the conversations. Furthermore, a comprehensive analysis is conducted to identify the correlation between emotions expressed by students and the discussed topics with their performance in the course in terms of their grades. Application Design: The student’s performance is formatively evaluated, taking into account a combination of their scores in various components. The core of the developed model comprises a speech transcriber module, an emotion analysis module, and a topic extraction module. The outputs of all these modules are processed to identify the correlations. Findings: The findings show a strong positive correlation between the expressed emotions of “relief” and “satisfaction” with students’ grades and a strong negative correlation between “frustration” and grades. Data also shows a strong positive correlation between course-related topics discussed in teams and grades and a strong negative correlation between noncourse-related topics and grades.
{"title":"Exploring the Influence of Emotional States in Peer Interactions on Students’ Academic Performance","authors":"Nasrin Dehbozorgi;Mourya Teja Kunuku","doi":"10.1109/TE.2023.3335171","DOIUrl":"https://doi.org/10.1109/TE.2023.3335171","url":null,"abstract":"Contribution: An AI model for speech emotion recognition (SER) in the educational domain to analyze the correlation between students’ emotions, discussed topics in teams, and academic performance.Background: Research suggests that positive emotions are associated with better academic performance. On the other hand, negative emotions have a detrimental impact on academic achievement. This highlights the importance of taking into account the emotional states of the students to promote a supportive learning environment and improve their motivation and engagement. This line of research allows the development of tools that allow educators to address students’ emotional needs and provide timely support and interventions. Intended Outcome: This work analyzes students’ conversations and their expressed emotions as they work on class activities in teams and investigates if their conversations are course-related or not by applying topic extraction to the conversations. Furthermore, a comprehensive analysis is conducted to identify the correlation between emotions expressed by students and the discussed topics with their performance in the course in terms of their grades. Application Design: The student’s performance is formatively evaluated, taking into account a combination of their scores in various components. The core of the developed model comprises a speech transcriber module, an emotion analysis module, and a topic extraction module. The outputs of all these modules are processed to identify the correlations. Findings: The findings show a strong positive correlation between the expressed emotions of “relief” and “satisfaction” with students’ grades and a strong negative correlation between “frustration” and grades. Data also shows a strong positive correlation between course-related topics discussed in teams and grades and a strong negative correlation between noncourse-related topics and grades.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141245022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anne Wrobetz;Kirsten Davis;Mayra S. Artiles;Homero Murzi
Contribution: Longitudinal video reflections are a unique approach to assessing student learning in study abroad. This study utilizes this method to understand the experiences of ten engineering students. The results show how their learning experiences changed over time and how the students connected these experiences to culture and engineering. Background: Study abroad research has demonstrated that students learn through a variety of experiences while abroad, but this research has been limited by narrow assessments, limited longitudinal data, and a lack of connection to engineering. This study uses longitudinal video reflections to explore student experiences in study abroad programs in a holistic way, capturing a wide range of learning outcomes over time. Research Questions: What types of significant experiences do engineering students abroad discuss in weekly reflection videos? How do engineering students abroad connect their significant experiences to engineering? Methodology: The critical incident technique (CIT) was used to collect video reflections from ten students for 14 weeks during a semester abroad. Their experiences were characterized using CIT methods and tracked shifts in incident types over time. The results show which types of experiences resulted in students reflecting deeply about cultural learning and engineering learning. Findings: The experiences students described in their videos shifted from a focus on communication and environmental factors early on to more cross-cultural comparison later in the program. Certain types of incidents resulted in cultural reflection, while others led to engineering learning. Communication incidents often served as a connecting point between engineering and cultural learning.
{"title":"Engineering Students Learning Abroad: Experiences Captured via Longitudinal Video Reflections","authors":"Anne Wrobetz;Kirsten Davis;Mayra S. Artiles;Homero Murzi","doi":"10.1109/TE.2023.3337783","DOIUrl":"https://doi.org/10.1109/TE.2023.3337783","url":null,"abstract":"Contribution: Longitudinal video reflections are a unique approach to assessing student learning in study abroad. This study utilizes this method to understand the experiences of ten engineering students. The results show how their learning experiences changed over time and how the students connected these experiences to culture and engineering. Background: Study abroad research has demonstrated that students learn through a variety of experiences while abroad, but this research has been limited by narrow assessments, limited longitudinal data, and a lack of connection to engineering. This study uses longitudinal video reflections to explore student experiences in study abroad programs in a holistic way, capturing a wide range of learning outcomes over time. Research Questions: What types of significant experiences do engineering students abroad discuss in weekly reflection videos? How do engineering students abroad connect their significant experiences to engineering? Methodology: The critical incident technique (CIT) was used to collect video reflections from ten students for 14 weeks during a semester abroad. Their experiences were characterized using CIT methods and tracked shifts in incident types over time. The results show which types of experiences resulted in students reflecting deeply about cultural learning and engineering learning. Findings: The experiences students described in their videos shifted from a focus on communication and environmental factors early on to more cross-cultural comparison later in the program. Certain types of incidents resulted in cultural reflection, while others led to engineering learning. Communication incidents often served as a connecting point between engineering and cultural learning.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141245204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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