Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028618
Pedro David Netto Silveira, D. Cury, C. S. Menezes, Otávio Lube dos Santos
This Research Full Paper presents recent research on the Educational Data Mining (EDM) field. In recent years, EDM has contributed significantly to the prevention of various challenges in academia. This paper presents an analysis of classifiers for a comparative study of EDM impact, using institutional data and trace data generated by a virtual learning environment to predict academic success/failure. For this, a model of educational data mining using logistic regression, support vector machine, naive bayes and J48 as classifiers and cross validation as a test method, was elaborated and was used to compare the prediction accuracy and the execution time of each classifier. The model was applied on a public dataset with 32,593 students, distributed among seven courses. The results on accuracy and execution time of each classifier allowed us to make recommendations on the suitability of using them. The results also revealed that it is better to separate the trace data from the institutional data in the model application regardless of the classifier. (Abstract)
{"title":"Analysis of classifiers in a predictive model of academic success or failure for institutional and trace data","authors":"Pedro David Netto Silveira, D. Cury, C. S. Menezes, Otávio Lube dos Santos","doi":"10.1109/FIE43999.2019.9028618","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028618","url":null,"abstract":"This Research Full Paper presents recent research on the Educational Data Mining (EDM) field. In recent years, EDM has contributed significantly to the prevention of various challenges in academia. This paper presents an analysis of classifiers for a comparative study of EDM impact, using institutional data and trace data generated by a virtual learning environment to predict academic success/failure. For this, a model of educational data mining using logistic regression, support vector machine, naive bayes and J48 as classifiers and cross validation as a test method, was elaborated and was used to compare the prediction accuracy and the execution time of each classifier. The model was applied on a public dataset with 32,593 students, distributed among seven courses. The results on accuracy and execution time of each classifier allowed us to make recommendations on the suitability of using them. The results also revealed that it is better to separate the trace data from the institutional data in the model application regardless of the classifier. (Abstract)","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"31 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81676122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028545
Mariela Mizota Tamada, J. F. D. M. Netto, D. P. R. D. Lima
Context: This Research to Practice Full Paper presents a systematic review of methodologies that propose ways of reducing dropout rate in Virtual Learning Environments (VLE). This generates large amounts of data about courses and students, whose analysis requires the use of computational analytical tools. Most educational institutions claim that the greatest issue in virtual learning courses is high student dropout rates. Goal: Our study aims to identify solutions that use Machine Learning (ML) techniques to reduce these high dropout rates. Method: We conducted a systematic review to identify, filter and classify primary studies. Results: The initial search of academic databases resulted in 199 papers, of which 13 papers were included in the final analysis. The review reports the historical evolution of the publications, the Machine Learning techniques used, the characteristics of data used, as well as identifies solutions proposed to reduce dropout in distance learning. Conclusion: Our study provides an overview of the state of the art of solutions proposed to reduce dropout rates using ML techniques and may guide future studies and tool development.
{"title":"Predicting and Reducing Dropout in Virtual Learning using Machine Learning Techniques: A Systematic Review","authors":"Mariela Mizota Tamada, J. F. D. M. Netto, D. P. R. D. Lima","doi":"10.1109/FIE43999.2019.9028545","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028545","url":null,"abstract":"Context: This Research to Practice Full Paper presents a systematic review of methodologies that propose ways of reducing dropout rate in Virtual Learning Environments (VLE). This generates large amounts of data about courses and students, whose analysis requires the use of computational analytical tools. Most educational institutions claim that the greatest issue in virtual learning courses is high student dropout rates. Goal: Our study aims to identify solutions that use Machine Learning (ML) techniques to reduce these high dropout rates. Method: We conducted a systematic review to identify, filter and classify primary studies. Results: The initial search of academic databases resulted in 199 papers, of which 13 papers were included in the final analysis. The review reports the historical evolution of the publications, the Machine Learning techniques used, the characteristics of data used, as well as identifies solutions proposed to reduce dropout in distance learning. Conclusion: Our study provides an overview of the state of the art of solutions proposed to reduce dropout rates using ML techniques and may guide future studies and tool development.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"23 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82128597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028672
M. P. D. Lovati, C. Z. Aguiar, T. Gava, D. Cury
This Research to Practice Full Paper Presents Debate with Maps: A new pedagogical architecture based on meaningful learning. Group Work is a didactic that has the objective of promoting learning and that can be of diverse natures. One of the determining factors for its success is the applied composition strategy, which may or may not favor the construction of knowledge of different profiles of learners. On the other hand, the task of composing groups of learners based on their cognitive performance, without the use of a support tool, can be very time-consuming. Therefore, the Pedagogical Architectures then emerge as teaching-learning structures that are made of several components which have the function of facilitating the interactions in an environment of autonomous action and collaborative construction. Teaching strategies that provide the learner with situations of questioning and imbalance are recognized as effective for the construction of new knowledge. However, leaving the responsibility for provoking such situations only to the teachers, overloads them. Therefore, we propose the Debate of Maps as a new instantiation of Pedagogical Architectures that uses concept maps as form of representation and sharing of knowledge in place of discursive responses in the debate dynamics. A tool was designed and added to a concept mapping service platform. Two experiments were carried out in the classroom environment, allowing a deep analysis on the application of the PA and tool. The tool supported the activity as a whole, with positive feedback from both the teacher and learners, concluding that the final maps had their contents improved.
{"title":"Debate with Maps: A new Pedagogical Architecture","authors":"M. P. D. Lovati, C. Z. Aguiar, T. Gava, D. Cury","doi":"10.1109/FIE43999.2019.9028672","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028672","url":null,"abstract":"This Research to Practice Full Paper Presents Debate with Maps: A new pedagogical architecture based on meaningful learning. Group Work is a didactic that has the objective of promoting learning and that can be of diverse natures. One of the determining factors for its success is the applied composition strategy, which may or may not favor the construction of knowledge of different profiles of learners. On the other hand, the task of composing groups of learners based on their cognitive performance, without the use of a support tool, can be very time-consuming. Therefore, the Pedagogical Architectures then emerge as teaching-learning structures that are made of several components which have the function of facilitating the interactions in an environment of autonomous action and collaborative construction. Teaching strategies that provide the learner with situations of questioning and imbalance are recognized as effective for the construction of new knowledge. However, leaving the responsibility for provoking such situations only to the teachers, overloads them. Therefore, we propose the Debate of Maps as a new instantiation of Pedagogical Architectures that uses concept maps as form of representation and sharing of knowledge in place of discursive responses in the debate dynamics. A tool was designed and added to a concept mapping service platform. Two experiments were carried out in the classroom environment, allowing a deep analysis on the application of the PA and tool. The tool supported the activity as a whole, with positive feedback from both the teacher and learners, concluding that the final maps had their contents improved.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"9 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80649391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028360
A. Gates, E. Villa, S. Hug, C. Convertino, Johannes Strobel
This Innovative Practice Work-In-Progress paper elucidates the approach of the NSF-funded CAHSI INCLUDES Alliance for creating change in students’ competencies by an effort across eight institutions to support the delivery of one-and two-credit hour courses for three levels of problem solving in Computer Science: general problem solving, computational thinking in problem solving, and algorithmic thinking in problem solving. The courses were developed to address industry’s need for improved problem-solving skills, incorporating consistent, deep collaboration with Google technical staff The first of its kind for CAHSI, the problem-solving courses are fewer credit hours than typical courses in order to fit within a traditional curriculum. The intent is to instill complementary problem-solving, computational thinking skills, and logical reasoning needed to succeed in computer science, and make this content available across different student populations at various stages in their academic pathways. Advanced problem solving prepares students for competitive interviews. The courses create opportunities to learn across academic levels, and create new student communities, mentorship opportunities, and social connections to support retention. The paper reports on the course design, student reflection, assessment and evaluation, and an ethnographic study of the courses.
{"title":"A National INCLUDES Alliance Effort to Integrate Problem-Solving Skills into Computer Science Curriculum","authors":"A. Gates, E. Villa, S. Hug, C. Convertino, Johannes Strobel","doi":"10.1109/FIE43999.2019.9028360","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028360","url":null,"abstract":"This Innovative Practice Work-In-Progress paper elucidates the approach of the NSF-funded CAHSI INCLUDES Alliance for creating change in students’ competencies by an effort across eight institutions to support the delivery of one-and two-credit hour courses for three levels of problem solving in Computer Science: general problem solving, computational thinking in problem solving, and algorithmic thinking in problem solving. The courses were developed to address industry’s need for improved problem-solving skills, incorporating consistent, deep collaboration with Google technical staff The first of its kind for CAHSI, the problem-solving courses are fewer credit hours than typical courses in order to fit within a traditional curriculum. The intent is to instill complementary problem-solving, computational thinking skills, and logical reasoning needed to succeed in computer science, and make this content available across different student populations at various stages in their academic pathways. Advanced problem solving prepares students for competitive interviews. The courses create opportunities to learn across academic levels, and create new student communities, mentorship opportunities, and social connections to support retention. The paper reports on the course design, student reflection, assessment and evaluation, and an ethnographic study of the courses.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"42 5-7 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77724450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028531
C. Finelli, J. Mondisa
This Innovative Practice, Full Paper describes a graduate course we developed to introduce students to the field of engineering education research (EER). The 3-credit course – EER 601: Foundations of Engineering Education Research – is the first required course of a brand new EER graduate program at the University of Michigan. The graduate program is part of a unique initiative that includes five tenured/tenure-track EER faculty who are embedded in traditional engineering departments. The primary area of scholarship for these faculty is EER, but they teach courses in and support the goals and mission of both their home engineering departments and the EER program. EER 601 is designed as a required course for students in the EER program, for other students supported by the EER faculty, and for interested students across the university. In this paper, we provide details of the course content, assignments, structure, and logistics for EER 601. We also present several sources of evidence to demonstrate how the course achieved two key course goals. Finally, we describe revisions we plan to make to the course.
{"title":"An innovative graduate course in engineering education research: How well does it meet course goals?","authors":"C. Finelli, J. Mondisa","doi":"10.1109/FIE43999.2019.9028531","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028531","url":null,"abstract":"This Innovative Practice, Full Paper describes a graduate course we developed to introduce students to the field of engineering education research (EER). The 3-credit course – EER 601: Foundations of Engineering Education Research – is the first required course of a brand new EER graduate program at the University of Michigan. The graduate program is part of a unique initiative that includes five tenured/tenure-track EER faculty who are embedded in traditional engineering departments. The primary area of scholarship for these faculty is EER, but they teach courses in and support the goals and mission of both their home engineering departments and the EER program. EER 601 is designed as a required course for students in the EER program, for other students supported by the EER faculty, and for interested students across the university. In this paper, we provide details of the course content, assignments, structure, and logistics for EER 601. We also present several sources of evidence to demonstrate how the course achieved two key course goals. Finally, we describe revisions we plan to make to the course.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"96 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75886949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028565
H. Perkins, Marissa A. Tsugawa-Nieves, M. Bahnson, D. Satterfield, Mackenzie Parker, Adam Kirn, C. Cass
The purpose of this full-length research paper is to explore the motivation profiles of engineering doctoral students (EDS) and their effects on student persistence. A Latent Profile Analysis (LPA) identified five profiles across four constructs from the Future Time Perspective (FTP) framework, with three straightforward profiles (Low, Average, and High) and two mixed profiles (Low Connectedness and Low Multiplicity). Two between-subjects ANCOVAs were run to test for differences in difficulty ascertaining degree progress (DADP) and intentions to persist (IP). DADP differed significantly by profile assignment, F(4,1137) = 21.38, p <.001, Partial-eta squared =.07, as did IP, F(4,1136) = 12.26, p <.001, Partial-eta squared =.04. This indicates that there are distinct motivation profiles among EDS with implications for student progress and persistence. Differences between the five profiles and their effect on DADP and IP will be discussed in further detail, along with recommendations for faculty and advisors.
本研究旨在探讨工科博士生的学习动机及其对学生坚持学习的影响。潜在特征分析(LPA)从未来时间视角(FTP)框架中确定了四种结构中的五种特征，其中三种直接特征(低、平均和高)和两种混合特征(低连通性和低多样性)。使用两个受试者间ANCOVAs来测试确定程度进展(DADP)和坚持意图(IP)的难度差异。不同剖面分配的DADP差异显著，F(4,1137) = 21.38, p <。001，偏平方=。07, IP也一样，F(4,1136) = 12.26, p <。001，偏平方=。04。这表明在EDS学生中存在不同的动机特征，对学生的进步和坚持有影响。五种概况之间的差异及其对DADP和IP的影响将进一步详细讨论，以及对教师和顾问的建议。
{"title":"Motivation Profiles of Engineering Doctoral Students and Implications for Persistence","authors":"H. Perkins, Marissa A. Tsugawa-Nieves, M. Bahnson, D. Satterfield, Mackenzie Parker, Adam Kirn, C. Cass","doi":"10.1109/FIE43999.2019.9028565","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028565","url":null,"abstract":"The purpose of this full-length research paper is to explore the motivation profiles of engineering doctoral students (EDS) and their effects on student persistence. A Latent Profile Analysis (LPA) identified five profiles across four constructs from the Future Time Perspective (FTP) framework, with three straightforward profiles (Low, Average, and High) and two mixed profiles (Low Connectedness and Low Multiplicity). Two between-subjects ANCOVAs were run to test for differences in difficulty ascertaining degree progress (DADP) and intentions to persist (IP). DADP differed significantly by profile assignment, F(4,1137) = 21.38, p <.001, Partial-eta squared =.07, as did IP, F(4,1136) = 12.26, p <.001, Partial-eta squared =.04. This indicates that there are distinct motivation profiles among EDS with implications for student progress and persistence. Differences between the five profiles and their effect on DADP and IP will be discussed in further detail, along with recommendations for faculty and advisors.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"10 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81589427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028506
Andreas Mai, P. Scholz, G. Fischer, F. Gerfers
This paper presents a novel concept for educating future nano- and microelectronic engineers and IC-designers. An educational model for the full spectrum of the microelectronics value chain is presented, as well as the successful implementation of this model in the authors’ curriculum. Main intention of this model is that students develop their own integrated circuits (ICs) based on a SiGe-BiCMOS technology for mm-wave applications, simulate functionality of the complex ICs by dedicated software tools, get an insight of their production and conclude their work in a final verification and characterization of the ICs. Finally, this educational model serves the way from basic knowledge to application in the rapidly growing business of micro- and nanoelectronics.
{"title":"High Performance Electronic Design Education - from Technology towards High Frequency Chip Sets","authors":"Andreas Mai, P. Scholz, G. Fischer, F. Gerfers","doi":"10.1109/FIE43999.2019.9028506","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028506","url":null,"abstract":"This paper presents a novel concept for educating future nano- and microelectronic engineers and IC-designers. An educational model for the full spectrum of the microelectronics value chain is presented, as well as the successful implementation of this model in the authors’ curriculum. Main intention of this model is that students develop their own integrated circuits (ICs) based on a SiGe-BiCMOS technology for mm-wave applications, simulate functionality of the complex ICs by dedicated software tools, get an insight of their production and conclude their work in a final verification and characterization of the ICs. Finally, this educational model serves the way from basic knowledge to application in the rapidly growing business of micro- and nanoelectronics.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"26 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82492953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028529
F. Vahid, Alex D. Edgcomb, Roman L. Lysecky, Y. Rajasekhar
This innovative practice full paper presents new learning content, developed natively for the web, that teaches core programming concepts using interactive activities, such as animations, learning questions, and interactive tools, in addition to text and figures. The core programming concepts are topics typically covered in CS1 (and often in CS0), including input/output, variables, branching, loops, arrays, and functions. Usually, programming is introduced with an industry language, such as Java or Python, which were developed for professionals, not for students. Sometimes, programming is introduced visually, such as Scratch or Alice, but many instructors want a more serious feel for college students, writing textual code. Our content teaches programming using an ultra-simple language, Coral, designed specifically to teach core concepts. The content presents a Coral program as code or a flowchart that closely resembles the code’s structure. Each chapter starts by introducing the programming concept visually with flowchart examples, so students develop a strong ability to read a program and understand how the program executes. Later in the chapter, the content introduces the corresponding textual code. The student then writes code to solve homework problems. Such incremental learning (first master program reading, then master program writing) is a key feature. Another key feature is a strong emphasis on visualization and intuition: The content uses animations that show Coral programs being executed line-by-line, along with variables shown in memory, including variable value updates from assignments. Further, the content has an online educational simulator where a student or instructor can write and execute Coral code. This paper includes early student usage data, such as amount of time spent to complete learning and homework, that shows students can quickly learn programming concepts. Some surveyed students commented on liking the incremental practice.
{"title":"New web-based learning content for core programming concepts using Coral","authors":"F. Vahid, Alex D. Edgcomb, Roman L. Lysecky, Y. Rajasekhar","doi":"10.1109/FIE43999.2019.9028529","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028529","url":null,"abstract":"This innovative practice full paper presents new learning content, developed natively for the web, that teaches core programming concepts using interactive activities, such as animations, learning questions, and interactive tools, in addition to text and figures. The core programming concepts are topics typically covered in CS1 (and often in CS0), including input/output, variables, branching, loops, arrays, and functions. Usually, programming is introduced with an industry language, such as Java or Python, which were developed for professionals, not for students. Sometimes, programming is introduced visually, such as Scratch or Alice, but many instructors want a more serious feel for college students, writing textual code. Our content teaches programming using an ultra-simple language, Coral, designed specifically to teach core concepts. The content presents a Coral program as code or a flowchart that closely resembles the code’s structure. Each chapter starts by introducing the programming concept visually with flowchart examples, so students develop a strong ability to read a program and understand how the program executes. Later in the chapter, the content introduces the corresponding textual code. The student then writes code to solve homework problems. Such incremental learning (first master program reading, then master program writing) is a key feature. Another key feature is a strong emphasis on visualization and intuition: The content uses animations that show Coral programs being executed line-by-line, along with variables shown in memory, including variable value updates from assignments. Further, the content has an online educational simulator where a student or instructor can write and execute Coral code. This paper includes early student usage data, such as amount of time spent to complete learning and homework, that shows students can quickly learn programming concepts. Some surveyed students commented on liking the incremental practice.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83355760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028636
Nasrin Dehbozorgi, S. Macneil
This work-in-progress paper proposes a semiautomated method to analyze students’ reflections. It is challenging to include reflection activities in computing classes because of the amount of time required from students to answer the reflection questions and the amount of effort required for instructors to review the students’ responses. These challenges inspired us to adopt Digital Minute Paper (DMP) as a way to give students multiple, quick opportunities to stop and reflect on their experiences in class. In this way, students are given an opportunity to develop metacognitive skills and to potentially improve their performance in the class. In addition, we used these DMPs as formative feedback for the instructors to address students’ problems in the class and to continuously improve the course design. Reading reflections is tedious, time-consuming, and does not scale to large classes. To extract insights from the DMPs, we created a semi-automated process for analyzing DMPs by applying natural language processing (NLP). Our process extracts unigrams and bigrams from the reflections and then visualizes related quotes from the reflections using a treemap visualization. We found that this semi-automatic analysis of the reflections is a good, low-effort way to capture student feedback in addition to helping students be more self-regulating learners.
{"title":"Semi-automated Analysis of Reflections as a Continuous Course","authors":"Nasrin Dehbozorgi, S. Macneil","doi":"10.1109/FIE43999.2019.9028636","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028636","url":null,"abstract":"This work-in-progress paper proposes a semiautomated method to analyze students’ reflections. It is challenging to include reflection activities in computing classes because of the amount of time required from students to answer the reflection questions and the amount of effort required for instructors to review the students’ responses. These challenges inspired us to adopt Digital Minute Paper (DMP) as a way to give students multiple, quick opportunities to stop and reflect on their experiences in class. In this way, students are given an opportunity to develop metacognitive skills and to potentially improve their performance in the class. In addition, we used these DMPs as formative feedback for the instructors to address students’ problems in the class and to continuously improve the course design. Reading reflections is tedious, time-consuming, and does not scale to large classes. To extract insights from the DMPs, we created a semi-automated process for analyzing DMPs by applying natural language processing (NLP). Our process extracts unigrams and bigrams from the reflections and then visualizes related quotes from the reflections using a treemap visualization. We found that this semi-automatic analysis of the reflections is a good, low-effort way to capture student feedback in addition to helping students be more self-regulating learners.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"54 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78667702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/FIE43999.2019.9028447
M. Alzayed
Empathy has proven to be an effective driver of design outcomes and thus is seen as a core constituent of engineering design education. While prior work underscores the importance of empathy in engineering and identifies the factors that lead students to become more empathic, many studies have relied on students’ perceptions of their empathy and most were conducted as controlled experimental workshops. Therefore, the main objective of this research is to identify the factors that contribute to the building of empathy in engineering design education and the subsequent impact on engineering design performance. This goal will be achieved through a longitudinal study with 103 first-year engineering design students that aims to identify the predictive validity of students’ individual traits on empathy development, understand the relationship between empathy development and students’ design performance, and investigate the impact of team composition on team empathy development. The results from this research would better inform pedagogical interventions aimed at empathy development.
{"title":"An Exploration of the Role of Student Empathy in Engineering Design Education","authors":"M. Alzayed","doi":"10.1109/FIE43999.2019.9028447","DOIUrl":"https://doi.org/10.1109/FIE43999.2019.9028447","url":null,"abstract":"Empathy has proven to be an effective driver of design outcomes and thus is seen as a core constituent of engineering design education. While prior work underscores the importance of empathy in engineering and identifies the factors that lead students to become more empathic, many studies have relied on students’ perceptions of their empathy and most were conducted as controlled experimental workshops. Therefore, the main objective of this research is to identify the factors that contribute to the building of empathy in engineering design education and the subsequent impact on engineering design performance. This goal will be achieved through a longitudinal study with 103 first-year engineering design students that aims to identify the predictive validity of students’ individual traits on empathy development, understand the relationship between empathy development and students’ design performance, and investigate the impact of team composition on team empathy development. The results from this research would better inform pedagogical interventions aimed at empathy development.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"10 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90109659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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