{"title":"Do Badges Increase Student Engagement and Motivation?","authors":"D. Dicheva, Rebecca Caldwell, Breonte Guy","doi":"10.1145/3368308.3415393","DOIUrl":"https://doi.org/10.1145/3368308.3415393","url":null,"abstract":"Gamification - using game mechanics for affording gameful experiences in non-game contexts - is getting increased attention in the educational field. However, its motivational mechanisms, intended to enhance student learning, are still not sufficiently understood. In this paper, we present an empirical study on the use of one of the most popular gamification elements, badges. The goal is to shed some light on their impact on student engagement and motivation. The study results suggest that while the badges improve student engagement and academic performance, they do not affect the student's intrinsic motivation. However, we speculate that they foster internalization of the learning-related extrinsic motivators? values, which results in increased engagement in the learning activities.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128719205","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":"On Validity of Sentiment Analysis Scores and Development of Classification Model for Student-Lecturer Comments Using Weight-based Approach and Deep Learning","authors":"Ochilbek Rakhmanov","doi":"10.1145/3368308.3415361","DOIUrl":"https://doi.org/10.1145/3368308.3415361","url":null,"abstract":"In this paper, a novel state-of-art classification method was presented for student-lecturer comment classification. Tf-Idf was used to assign weights for each word and several different ANN structures were tested. A large dataset, 52571 comments, was used during training. The results show that developed models clearly overperformed existing classification models in this field. 97% of prediction accuracy was achieved on 3-class dataset, while the prediction accuracy for 5-class dataset was 92%.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127488187","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":"Interpretable Deep Learning for University Dropout Prediction","authors":"Máté Baranyi, Marcell Nagy, Roland Molontay","doi":"10.1145/3368308.3415382","DOIUrl":"https://doi.org/10.1145/3368308.3415382","url":null,"abstract":"The early identification of college students at risk of dropout is of great interest and importance all over the world, since the early leaving of higher education is associated with considerable personal and social costs. In Hungary, especially in STEM undergraduate programs, the dropout rate is particularly high, much higher than the EU average. In this work, using advanced machine learning models such as deep neural networks and gradient boosted trees, we aim to predict the final academic performance of students at the Budapest University of Technology and Economics. The dropout prediction is based on the data that are available at the time of enrollment. In addition to the predictions, we also interpret our machine learning models with the help of state-of-the-art interpretable machine learning techniques such as permutation importance and SHAP values. The accuracy and AUC of the best-performing deep learning model are 72.4% and 0.771, respectively that slightly outperforms XGBoost, the cutting-edge benchmark model for tabular data.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126540490","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}
D. Orn, Lian Duan, Yi-tao Liang, Harvey P. Siy, M. Subramaniam
{"title":"Agro-AI Education: Artificial Intelligence for Future Farmers","authors":"D. Orn, Lian Duan, Yi-tao Liang, Harvey P. Siy, M. Subramaniam","doi":"10.1145/3368308.3415457","DOIUrl":"https://doi.org/10.1145/3368308.3415457","url":null,"abstract":"The importance of sustainable and efficient food production has driven the need for applying increasingly advanced approaches in farming and agriculture. To keep up with this need, farmers and future farmers need to be trained in the ways of precision agriculture. With the widespread use of artificial intelligence across all industries, it is not surprising to find AI at the heart of precision agriculture. While AI has brought a lot of promise, it has also brought a lot of dread, due to the lack of understanding about what it is and what it can do. To help farmers buy into applying AI, a new educational program is needed. To this end, we have developed a simple active learning system to illustrate AI, particularly, machine learning. We present an overview of the system and discuss how it can contribute to future farmers' understanding of how AI works.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123436315","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":"Using the Pandemic as a Case Study: Teaching Social and Ethical Issues","authors":"Diane C. Shichtman","doi":"10.1145/3368308.3415390","DOIUrl":"https://doi.org/10.1145/3368308.3415390","url":null,"abstract":"The efforts to control the COVID-19 pandemic present a living case that is unfortunate but well-suited for addressing the global professional practice and social responsibility domains of IT2017. It provides an ideal assignment for discussion, and as an open-ended case study, lends itself well to that discussion taking place in a multiweek, asynchronous online mode, should that be necessary.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123436360","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":"Teaching from Home: Network Support Perspectives","authors":"Jianping Pan","doi":"10.1145/3368308.3415431","DOIUrl":"https://doi.org/10.1145/3368308.3415431","url":null,"abstract":"In this paper, we examine the challenges of \"teaching from home'' due to CoViD-19 with the viewpoint of information technology (IT) education in general and computer network support in particular, and offer some suggestions through our experience in Spring and Summer 2020 with input from IT support professionals, to create the very needed discussion among educators on this timely topic, which can be useful for Fall 2020 and beyond. Online teaching may become a considerable mode of course delivery in the post-pandemic era, even without another similar event.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121845738","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}
Edward J. Glantz, Michael R. Bartolacci, M. Nasereddin, D. Fusco
{"title":"Cross-Boundary Cyber Education Design","authors":"Edward J. Glantz, Michael R. Bartolacci, M. Nasereddin, D. Fusco","doi":"10.1145/3368308.3415374","DOIUrl":"https://doi.org/10.1145/3368308.3415374","url":null,"abstract":"This paper provides a cross-boundary process to guide colleges and universities creating undergraduate cyber curriculum or reviewing established programs. There is growing demand for academic institutions to help close the skills gap by developing cyber curriculum preparing students for careers in cybersecurity. The cross-boundary process in this paper builds on a multi-level, multi-discipline approach previously used to launch a new undergraduate cyber program. This expanded approach recommends evaluating advisory consortium feedback, master's degree programs, certifications, and internal considerations (e.g., faculty expertise). This paper is prepared by cyber faculty at a university offering both residential and online general education courses as well as undergraduate and master's degrees in cybersecurity. This paper further advances the call for discussion on the topic of cyber education.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125249018","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":"ITEval","authors":"Xinli Wang, M. El-Said, Paul M. Leidig","doi":"10.1145/3368308.3415402","DOIUrl":"https://doi.org/10.1145/3368308.3415402","url":null,"abstract":"We present a framework of an integrated model, referenced as ITEval, to comprehensively assess and quantitatively compare products of information technology. In this model, we assume that the adoption of technology by an organization is determined by user's willingness to use it, the total cost to own it and its environmental influence. Approaches to quantifying these factors are discussed. Different methods are proposed to analyze and integrate these determinants for assessment and comparison. An example study is employed to demonstrate its application.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122269665","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":"Outreach, Inreach, and The Age of Reason: Technology Education for a New Age of Learning","authors":"P. Seeling","doi":"10.1145/3368308.3415353","DOIUrl":"https://doi.org/10.1145/3368308.3415353","url":null,"abstract":"Educational institutions are in the middle of great changes following trends in demographics and broad availability of online education at comparatively infinitesimal costs for traditional and other students alike. While the response over time has been a combination of efforts we term Outreach and Inreach, we argue that a refreshed view on how education can be sustainably delivered in the future is required.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130299083","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":"Developing an Undergraduate Course Curriculum for Ethical Hacking","authors":"Yang Wang, Margaret McCoey, Qian Hu","doi":"10.1145/3368308.3415366","DOIUrl":"https://doi.org/10.1145/3368308.3415366","url":null,"abstract":"An Ethical Hacking (EH) course not only is a critical component for a Cybersecurity program but also an essential preparation for CS/IT majors towards career paths as security professionals. We face two major challenges when developing an undergraduate EH course, including the setup and choice of the lab design, and the choice and organization of covered topics for this course. On one hand, we have limited space, budget and technical support for a course that relies heavily on hands-on exercises. Given the nature of this course, the lab activities are often 'offensive' and lab operations demand administrative privileges, which cause compliance issues with the university's IT policies. On the other hand, given the vast variety of topics and the fast pace of the field, it is difficult to select and organize an essential set of knowledge units to ensure that students are exposed to current technologies and prepared to be industry-ready. We adopt two major design principles to address these challenges correspondingly. First, our choice of a hybrid Virtual Machine (VM)-based and Web-based labs provides students the full set of privileges to perform lab activities without posing threats to the campus network. The Web-based labs remove high cost of hardware and avoid overwhelming installations and configurations for the lab. Second, given the diversity of topics and fast developments in this field, we choose topics based on four criteria: representative, current, certification-related, and foundations for other covered concepts. The chosen topics are aligned with three EH certificates, and organized into twelve modules with clear inter-module and intra-module logic. This paper details the curriculum of this EH course and elaborates how our design principles are entailed in the course.","PeriodicalId":374890,"journal":{"name":"Proceedings of the 21st Annual Conference on Information Technology Education","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130809428","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}