2021 IEEE Frontiers in Education Conference (FIE)最新文献

{"title":"Predicting Student Performance Based on Logs in Moodle LMS","authors":"Mariela Mizota Tamada, Rafael Giusti, J. F. D. M. Netto","doi":"10.1109/FIE49875.2021.9637274","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637274","url":null,"abstract":"Context: This innovative practice full paper presents a methodology to predict at-risk students in the context of a course assisted by an LMS (Learning Management System). LMSs generate large amounts of data about courses and students, which allows schools to make useful insights with the help of computational analytical tools. Most educational institutions claim that the most significant issue in virtual learning is high student dropout rates, and school performance is one of its main factors. Objective: Our study aims to use Machine Learning techniques based on logs from the Modular Object-Oriented Dynamic Learning Environment (Moodle). Those data are used to analyze student behavior and create a model that helps detect students at risk. Method: This paper used institutional data and trace data generated by LMS of a Computing education technical courses, blended and distance learning, at high school. We compared 7 algorithms with models trained at 6%, 20%, 40%, and 60% of the course duration, with the intent of exploring the compromise between early and late detection of at-risk students. Our model has 69% positive classe (failed) and 31% negative class (passed), and the false positives cost is important. Results: The results show 7 created models of predicting. The findings for Random Forest performed the best when predicting a student's performance. Conclusion: Our study provides a student at-risk prediction model using ML techniques on logs in Moodle LMS and may guide future studies and tool development to reduce these high dropout rates.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"3 15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128979952","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}

{"title":"IS2020:Competency-Based Information Systems Curriculum Guidelines","authors":"V. Shankararaman, Paul M. Leidig, Greg Anderson, Mark F. Thouin","doi":"10.1109/FIE49875.2021.9637150","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637150","url":null,"abstract":"The Association of Computing Machinery (ACM) and the Association for Information Systems (AIS) engaged in a project to revise the Information Systems Curriculum. The IS2010 model curriculum has been widely used for nearly a decade. However, its value may be decreasing as new approaches to model curricula have been introduced. The AIS and ACM established an exploratory taskforce which found there have been substantial changes in the IS field, and that current graduates' technical skills do not appear to meet industry needs. The IS discipline must express its core in terms of a standard curriculum that meet stakeholder demands. A joint ACM/AIS taskforce on the Information Systems Model Curriculum (IS2020) was created to develop new IS curriculum guidelines. This panel will introduce the work of the IS2020 taskforce. Panelists will present the key points from the final report. This session should be of interest to faculty and administrators developing college-level curricula in IS.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128985341","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}

{"title":"Sketchnoting, a Visual Way to Improve Creative Confidence and Critical Thinking in the Virtual Environment","authors":"Verena Paepcke-Hjeltness, M. Mina","doi":"10.1109/FIE49875.2021.9637358","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637358","url":null,"abstract":"This Innovative Practice Workshop aims to expose engineering educators and students to the basics of sketchnoting as a creative and non-traditional visual listening and idea generation methodology. It has shown to foster in-class engagement during lectures especially in the virtual environment, when lectures are paced accordingly. When applied in an engineering learning environment it has been investigated to foster subject matter comprehension and retention; based on the premise that in order to visualize a concept it has to be understood. The session participants will actively learn, practice, and develop basic sketchnoting skills, addressing the conference theme of convergence in engineering education by exposing students and faculty to this low-fidelity visualization technique originated in design disciplines. The session will provide an introduction to the building blocks for visual notetaking focusing on engineering and scientific disciplines. The session will be interactive and hands-on covering the process from learning the basics, to developing an understanding for sketchnoting and how to apply it.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130634643","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}

{"title":"Educators' Perceptions of the Influence of Academic Environment on Ethics Education: A Comparative Case Study of Two Engineering Departments","authors":"M. Polmear, A. Bielefeldt, D. Knight","doi":"10.1109/FIE49875.2021.9637263","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637263","url":null,"abstract":"This full research paper explored the relationship between academic environment and faculty members' perspectives on ethics instruction. Ethical responsibility and awareness of the societal impacts of technology are crucial learning outcomes for future engineers. The study and practice of ethics are convergent since the subject draws on engineering and the humanities with the aim of positioning students to responsibly address the most pressing societal challenges. In the curriculum, faculty members' decisions regarding course content, including those related to ethics and societal impacts (ESI), result from a host of factors including influences at the department, college, and institutional levels. This exploratory study examined engineering faculty members' perception of their academic environment in relation to ESI education via a comparative case study of two engineering departments. The mixed-methods design included faculty interviews and surveys to understand participants' perceptions of culture, leadership, and curricular importance related to ESI. The study also employed document analysis to contextualize the formal inclusion of ESI and to triangulate the findings. The data suggested the influence that culture and leadership, especially at the department level, exert on perceptions of support for ESI instruction. Across both departments, the data indicated the high value that faculty place on ESI in engineering education. The findings suggest the importance of establishing both bottom-up and top-down support for ESI education and creating a culture in which espoused values align with formal structures and policies. With increasing attention paid to the inclusion of ESI and growing responsibility on engineering faculty, it is important to acknowledge the environment in which educators develop their instructional practices and perspectives.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130770180","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}

{"title":"Enhancing the Intelligence of the Adaptive Learning Software through an AI assisted Data Analytics on Students Learning Attributes with Unequal Weight","authors":"Yanzhen Qu, Olanrewaju Ogunkunle","doi":"10.1109/FIE49875.2021.9637387","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637387","url":null,"abstract":"Along with the growing popularity of the adaptive learning platform software in STEM education programs, further enhancing the ability of the adaptive learning platform to support learning effectiveness has become a priority. A common goal of all the adaptive learning platform software is to identify gaps in a student's knowledge, and provide relevant learning materials based on the result of the assessment of the student's exiting knowledge towards to the targeted subject, to increase the learning effectiveness. However, the student's existing knowledge is only one learning attribute, and it cannot reflect all the aspects that have an impact to the student's learning effectiveness. A natural solution to overcome this weakness is to make the adaptive learning decision making algorithm capable to process the dataset of multiple learning attributes of the student efficiently. This paper presents a machine learning algorithm to efficiently process the dataset of a student's multiple learning attributes. The main enabling foundation for this new algorithm is a data structure called “student learning attributes index” which represents every learning attribute as a tuple of three elements: the “learning-attribute-If)”, the “weight” of the learning attribute among all the learning attributes, and the “efficiency” of the contribution to the student's learning effectiveness made by the learning attribute. This study has applied unequal weight to each of the learning attributes, more accurately reflecting that different learning attributes will have different impacts on a student's learning effectiveness. This new algorithm enables various learning support applications to become more practical and accurate in supporting student learning.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132017910","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}

{"title":"Online Student Supervision: A Reflective Study on Lessons and Challenges","authors":"Ali Ahmed, C. Watterson, Karsten Lundqvist, Jennifer Ferreira","doi":"10.1109/FIE49875.2021.9637211","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637211","url":null,"abstract":"This Research to Practice Full Paper presents a reflective study showing the online teaching and advisory practices during Covid-19. Due to the COVID-19 pandemic, distance learning and active practices to engage online learners are now centre focused on educational institutions' everyday praxis. Tertiary educators have often struggled during enforced lockdowns to convert courses from face-to-face delivery to pure online delivery. This change has presented challenges in curriculum development as academics strive to achieve best practice. It is also challenging to design a pedagogically sound and engaging course for diverse students from a broad spectrum of educational backgrounds. Online classes often require unique infrastructures such as devices with specific tools or hardware requirements. This paper presents a reflective study showing the online teaching and advisory practices during Covid-19 by the first author while teaching and supervising Master of Science (MSc) dissertation students online at a top-ranked UK university (i.e. University of Liverpool). The first author has been involved in the programme for more than ten years. This university is called University A (Uni A) throughout this paper. The paper demonstrates Uni A students' journey from finding the dissertation advisor to completing the research project. It also discusses the class structure, the university policy and guidelines, teaching practices, and how student progress is managed and assessed. The paper then contrasts the first authors experience at Uni A with that of all authors (including the first author - who has been working at both universities) experience supervising postgraduate and honours students at a top New Zealand University (i.e. Victoria University of Wellington). This university is called University B (Uni B) throughout this paper. The lessons learnt from teaching a stream of students enrolled in a pure distance learning degree (i.e. deliberate online degree) at Uni A offers insight into how Uni B might better restructure its predominantly face-to-face degrees to support both online and in-person best practices.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132321854","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}

{"title":"Assignment Presentation Framework for CS1 Programming Problems","authors":"Rita Garcia","doi":"10.1109/FIE49875.2021.9637136","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637136","url":null,"abstract":"A Computer Science programming assignment is a core assessment tool used by educators to measure students' understanding of programming concepts. A well-structured programming assignment can assist students in comprehending a problem and help them develop problem-solving skills. This research focuses on the presentation of well-structured programming assignments to help with students' understanding of the problem, supporting educators in the development of these assignments. To create well-structured programming assignments, we performed a literature review to identify design treatments that help students better understand introductory programming (CS1) assignments. An illustration study was then used to test the assignments from the identified design treatments. The illustration study collected students' perspectives on how the design treatments improved the understanding of the assignment design. From this work, we developed a framework from the identified design treatments. The results for the illustration study showed the design treatments helped students identify the problem's requirements and realise what is required to solve the problem. Though our work was examined within the CS1 context, our findings may be useful to similar assignment contexts, such as helping students identify requirements for solving problems.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130953117","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}

{"title":"Building Design Experience and a Greater Sense of Community through an Integrated Design Project","authors":"J. Hamel, C. Strebinger, Erica Gilbertson, Yen-Lin Han, K. Cook, T. Shuman, Gregory S. Mason","doi":"10.1109/FIE49875.2021.9637480","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637480","url":null,"abstract":"WIP: The Mechanical Engineering (ME) Department at Seattle University was awarded a 2017 NSF RED (Revolutionizing Engineering and Computer Science Departments) grant. This award provided the opportunity to create a program where students and faculty are immersed in a culture of doing engineering with practicing engineers that in turn fosters an identity of being an engineer. Of the many strategies implemented to support this goal, one significant curricular change was the creation of a new multi-year design course sequence. This set of three courses, the integrated design project (IDP) sequence, creates an annual curricular-driven opportunity for students to interact with each other and professional engineers in the context of an open-ended design project. These three courses are offered to all departmental first-, second-, and third-year students simultaneously during the spring quarter each year. Each course consists of design-focused classroom instruction tailored to that class year, and a term design project that is completed by teams of students drawn from all three class years. This structure provides students with regular design education, while also creating a curricular space for students across the department to interact with and learn from one of another in a meaningful way. This structure not only prepares students for their senior design experience, but also builds a sense of community and belonging in the department. Furthermore, to support the “engineering with engineers” vision, volunteer engineers from industry participate as consultants in the design project activities, giving students the opportunity to learn from professionals regularly throughout their entire four years in the program. This course sequence was offered for the first time in 2020, and while the global pandemic impacted the experience, the initial offering was by all accounts a success. This paper provides an overview of the motivation for the three IDP courses, their format, objectives, and specific implementation details, and a discussion of some of the lessons learned. These particulars provide other engineering departments with a roadmap for how to implement this type of a curricular experience in their own programs.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125558683","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}

{"title":"Recommendation Model of Personalized Teaching Materials in E-Learning Environments","authors":"Thais Oliveira Almeida, J. F. D. M. Netto, Arcanjo Miguel Mota Lopes","doi":"10.1109/FIE49875.2021.9637286","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637286","url":null,"abstract":"This full paper of research category presents a proposal for a smart recommendation model to personalize the provision of teaching materials in Virtual Learning Environments (VLE), to continually learn from student feedback. This research presents a model that is divided into 4 parts: 1) Student model; 2) Domain model; 3) Mining module; and 4) Recommendation module. This research contributes to focus on the development of cognitive skills related to learning styles, aiming to help students understand the strengths and weaknesses of their cognitive and objective - cognitive strategies, with the construction of behavioral patterns generated from the exchange of messages information between the student and mining modules. It is hoped that with the implementation of e-learning models, this proposal can contribute to assist in guiding the teaching and learning process towards mastering a curriculum, with interactive regulations, and the acquisition of the corresponding skills through the discovery of knowledge and automation of the recommendation process. Besides, contributing to self-esteem and, mainly, helps to train professionals better prepared for the job market. Our focus is to describe complex processing of recommendations in e-learning environments in terms of knowledge, not the details of its implementation.","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126631035","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}

{"title":"Baskin Engineering Excellence Scholars Bridge Program: Planning, Implementation, and Evaluation","authors":"Narges Norouzi, Carmen Robinson, Rebecca Covarrubias, Ruby Hernandez, Danay Weldegabriel, Gwynn Benner, Wenjuan Sang, Rafael Espericueta","doi":"10.1109/FIE49875.2021.9637267","DOIUrl":"https://doi.org/10.1109/FIE49875.2021.9637267","url":null,"abstract":"In this Research to Practice Full Paper, we intend to share our experience in design, implementation, and evaluation of a summer bridge program for a group of first-year first-generation and underrepresented students entering engineering majors at the University of California Santa Cruz. Our program is proven to prepare students for engineering programming and mathematics courses, develop a growth mindset, build self-efficacy, and bond with the cohort to build peer-mentoring opportunities and increase a sense of belonging to the campus community and our school of engineering. We describe 1) program design and goals, 2) program schedule and curriculum (mathematics and programming), 3) description of research-based program evaluation, and 4) outline of research findings (both quantitatively and qualitatively).","PeriodicalId":408497,"journal":{"name":"2021 IEEE Frontiers in Education Conference (FIE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126739482","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}