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For the fortieth time, the Research and Theory Division of the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Jacksonville, Florida. The Proceedings of AECT's Convention are published in two volumes. Volume 1 contains 19 papers dealing primarily with research and development topics. Fourteen papers dealing with the practice of instructional technology including instruction and training issues are contained in Volume 2. Volume 1 contains the following 19 papers: (1) Gamification for Change: A New Approach to Investigate Students' Attitudes toward Educational Gamification in Online Learning Environments (Sumayah Abu-Dawood); (2) Facilitating Higher Levels of Thinking and Deeper Cognitive Processing of Course Text Using Reciprocal Teaching Strategies in Asynchronous Discussion Forums (Jenifer R. Marquis and Ginger S. Watson); (3) Online Learning Design and Implementation Models: A Model Validation Study Using Expert Instructional Designers (Ann Armstrong and Albert Gale); (4) Tracking the Design and Development of a Six Module miniMOOC for Quality Graduate Supervision (Hawazen Alharbi and Michele Jacobsen); (5) Diversity Training in Organization Settings: Effective and Ethical Approaches for Change Leaders (Ashley McArthur and Nancy B. Hastings); (6) Hey, Want to Play? "Kahooting" to Win the Learning Game (Papia Bawa); (7) An Examination of Prior Knowledge and Cueing Effects in an Animation (Ismahan Arslan-Ari); (8) Teacher Perceptions of the Adaptation of the New Computer Science (CS) Curriculum: An Evaluation of CS Curriculum Implementation (Suhkyung Shin, Jongpil Cheon, and Sungwon Shin); (9) Multimedia Video Resolution, Camera Angle, and the Impact on Instructor Credibility and Immediacy (Miguel Ramlatchan and Ginger S. Watson); (10) The Effects of Visible-Annotation Tool on the Learning Process and Learning Outcome in CSCL (Yoonhee Shin, Jaewon Jung, and Dongsik Kim); (11) Pre-Service ICT Teachers' Recommendations for School Internet Safety (Sanser Bulu, Melike Kavuk-Kalender, and Hafize Keser); (12) Turkish Schools' Readiness for Preventing Cyberbullying (Melike Kavuk-Kalender, Hafize Keser, and Sanser Bulu); (13) Examining Technology Integration Decision-Making Processes and Identifying Professional Development Needs of International Teachers (Medha Dalal, Leanna Archambault, and Catharyn Shelton); (14) Integrating Learning Analytics into Workforce Education to Develop Self-Assessment Competency (Lin Zhong); (15) Ensuring Academic Integrity in Online Courses: A Case Analysis in Three Testing Environments (Berhane Teclehaimanot, Sue Ann Hochberg, Diana Franz, Mingli Xiao, and Jiyu You); (16) Changing Student Performance and Perceptions through Productive Failure: Active Learning for Applied Chemistry in Pharmaceutics (Dan Cernusca and Sanku Mallik); (17) The Construction of Sentiment Lexicon in Educational Field Based on Word2vec (Xiang Feng and Longhui Qiu); (18) Blended Instruction by Using Simulation Method Teaching to Enhance Digital Literacy for Student Teachers in Thailand (Sumalee Chuachai); and (19) Social Network Use Preferences of Pre-Service ICT Teachers (Omer Faruk Islim and Nese Sevim Cirak). (Individual papers contain references.) [For Volume 2, see ED580817.]

These proceedings contain the papers and posters of the 5th International Conference on Educational Technologies 2017 (ICEduTech 2017), which has been organised by the International Association for Development of the Information Society and co-organised by the Western Sydney University, held in Sydney, Australia, 11-13 December 2017. ICEduTech is the scientific conference addressing the real topics as seen by teachers, students, parents and school leaders. Scientists, professionals and institutional leaders are invited to be informed by experts, sharpen the understanding what education needs and how to achieve it. Full papers presented in these proceedings include: (1) Bibliometric Science Mapping as a Popular Trend: Chosen Examples of Visualisation of International Research Network Results (Eugenia Smyrnova-Trybulska, Nataliia Morze, Olena Kuzminska and Piet Kommers); (2) Optimize Knowledge Sharing, Team Effectiveness, and Individual Learning within the Flipped Team-Based Classroom (Chung-Kai Huang, Chun-Yu Lin, Zih-Cin Lin, Cui Wang and Chia-Jung Lin); (3) Design and Development of an Interactive Multimedia Simulation for Augmenting the Teaching and Learning of Programming Concepts (Leonah L. Baloyi, Sunday O. Ojo and Etienne A. Van Wyk); (4) Introducing Tablets in a Portuguese School: A Micool Project Case Study Analysis (Miriam Judge); (5) College Communicative Teaching and e-Learning: A Training Scheme (Charito G. Ong; (6) Tested Strategies for Recruiting and Retention of STEM Majors (Sadegh Davari, Sharon Perkins-Hall and Krishani Abeysekera); (7) Redesigning Learning Spaces: What do Teachers Want for Future Classrooms? (Neuza Pedro); (8) Peer Instructions and Use of Technological Tools. An Innovative Methodology for the Development of Meaningful Learning (Oriel A. Herrera and Patricia Mejías); (9) It Doesn't Matter What is in Their Hands: Understanding How Students Use Technology to Support, Enhance and Expand Their Learning in a Complex World (Peter Bryant); (10) A Comparative Study on Social Media Addiction of High School and University Students (Ali Simsek, Kemal Elciyar and Taner Kizilhan); (11) Computer Literacy Teaching Using Peer Learning and under the Confucian Heritage Cultural Settings of Macao, China (Kelvin Wong, Ana Neves and Joao Negreiros); (12) Applying Sensors to Investigate Gender Differences in Beginning Tennis Players (Chih-Hung Yu, Jye-Shyan Wang and Cheng-Chih Wu); (13) Using Arduino to Teach Programming to First-Year Computer Science Students (Wee Lum Tan, Sven Venema and Ruben Gonzalez); (14) Dimensions of Self-Perceived Employability in First Year IT Students (Amy Antonio and David Tuffley); (15) Challenges for a New Generation of STEM Students (Krishani Abeysekera, Sharon Perkins-Hall, Sadegh Davari and Amanda Smith Hackler); (16) Developing a Gesture-Based Game for Mentally Disabled People to Teach Basic Life Skills (Mohammad Javad Nazirzadeh, Kürsat Cagiltay and Necdet Karasu); (17) Learning Group Formation for Massive Open Online Courses (MOOCs) (Sankalp Prabhakar and Osmar R. Zaiane) and (18) ICE: An Automated Tool for Teaching Advanced C Programming (Ruben Gonzalez). Short papers presented include: (1) MOOC as a Laboratory of Culture Shock: Helping Non-U.S. Students Integrate into All-American Virtual Environment (Valeri Chukhlomin and Anant Deshpande); (2) The Use of Mobile Devices Outside of the Classroom for Self-Directed Learning among Female EFL Students in Saudi Arabia (Fatimah Albedah and Chwee Beng Lee); (3) Communication Scaffolds for Project Management in PBL (Shigeru Sasaki, Masayuki Arai, Kumiko Takai, Mitsuhiro Ogawa and Hiroyoshi Watanabe); (4) Digital Pedagogies for Teachers' CPD (Matthew Montebello); (5) Sensing Locally in the Global Environment: Using Sensors in Teachers' Education (Maria João Silva, António Almeida, Bianor Valente, Margarida Rodrigues and Vítor Manteigas); (6) The Use of a Digital Badge as an Indicator and a Motivator (Jun Iwata, John Telloyan, Lynne Murphy, Shudong Wang and John Clayton; (7) Exploring the Education Potential of Minecraft: The Case of 118 Elementary-School Students (Thierry Karsenti and Julien Bugmann); (8) Digital Story Creation: Its Impact towards Academic Performance (Charito G. Ong); and (9) Collaborative Peer Feedback (David A. Smith). Posters include: (1) A System for Class Reflection Using iPads for Real-Time Bookmarking of Feedbacks into Simultaneously Recorded Videos (Taira Nakajima); (2) Roles, Strategies, and Impact of MOOCs on Flipping Business Education (Chung-Kai Huang, Chun-Yu Lin, Zih-Cin Lin and Cui Wang); and (3) Gamifying Outdoor Social Inquiry Learning with Context-Aware Technology (Morris Siu-Yung Jong, Tom Chan, Vincent Tam and Ming-Tak Hue). Individual papers include references, and an Author Index is included.

In this study, the authors have developed a web-based programming exercise system currently implemented in classrooms. This system not only provides students with a web-based programming environment but also tracks the time spent on exercises, logging operations such as program editing, building, execution, and testing. Additionally, it records their results. For educators, the system offers insights into each student's progress, the evolution of their source code, and the instances of errors. While teachers find these functions beneficial, the method of providing feedback to students needs improvement. Immediate feedback is proven to be more effective for student learning. If the final course score could be predicted based on early data (e.g., from the 1st or 2nd week), students could adapt their study strategies accordingly. This paper demonstrates that one can predict the final score using the system's operational logs from the initial phases of the course. Furthermore, the score predictions can be revised weekly based on new class logs. We also explore the potential of offering tailored advice to students to enhance their final score. [For the full proceedings, see ED636095.]

This collection of 18 papers covers four broad areas of teaching and learning in higher education: innovative college teaching/learning strategies; effective classroom research/assessment activities; advanced classroom technology; and developing teaching and learning centers. Titles include: (1) "African American Students' Perceptions of Cooperative Learning Experiences" (Lillie Anderton-Lewis and Danny H. Pogue); (2) "Learning to Learn Is a Teachable Skill" (Joan B. Baker, et al.); (3) "The Florida Higher Education Consortium: A Mathematics, Science, Technology Collaboration" (Marianne Barnes, et al.); (4) "Directions in the Core Curriculum for Computer Science Majors" (Edward J. Conjura); (5) "Teacher Immediacy and Distance Learning: The Multicultural Dimension" (James M. Cunningham and Mary McLemore); (6) "Liberal Education in Technology Courses" (Diane Delisio and Cathy Bishop-Clark); (7) "Learning and Motivation Theory Applied to Instruction" (Paul Eggen); (8) "Bringing the New Technologies to Distance Learning: A British Perspective" (Joel Greenberg); (9) "A Model Program: Discipline-Specific Instruction for Graduate Teaching Assistants" (Penny L. Hammrich and Kerri Armstrong); (10) "Is Technology a Substitute for Preparation in Calculus I?" (Robert Jerrard, et al.); (11) "Science Teacher Preparation: Whose Knowledge Is It?" (Judith Johnson); (12) "Learning to Teach on Television: Implications for Beginners" (Norma MacRae and Darcey Cuffman); (13) "Integrating Science and the Humanities: Redefining the Preparation of Elementary Teachers" (Patricia A. Nelson); (14) "Will Success Spoil Distance Education?" (Leslie Purdy); (15) "Collaborative Planning to Improve Higher Education: System-Wide and Campus Initiatives" (Paul Spear); (16) "Generating a Positive Student Experience in Distance Learning Education" (Costas S. Spirou); (17) "Conceiving the Commons: An Interdisciplinary Approach to Environmental Literacy" (Linda Wallace, et al.); (18) "Active Learning Through Live Television: Reflections on Practice" (Michael F. Welsh). (All papers contain references.) (CH)

The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions (Pittsburgh 2010, Cordoba 2009 and Montreal 2008), and a series of workshops within the AAAI, AIED, EC-TEL, ICALT, ITS, and UM conferences. The increase of e-learning resources such as interactive learning environments, learning management systems, intelligent tutoring systems, and hypermedia systems, as well as the establishment of state databases of student test scores, has created large repositories of data that can be explored to understand how students learn. The EDM conference focuses on data mining techniques for using these data to address important educational questions. The broad collection of research disciplines ensures cross fertilization of ideas, with the central questions of educational research serving as a unifying focus. This publication presents the following papers: (1) Social Information Discovery (Barry Smyth); (2) On exploration and mining of data in educational practice (Erik-Jan van der Linden, Martijn Wijffelaars, Thomas Lammers); (3) EDM and the 4th Paradigm of Scientific Discovery--Reflections on the 2010 KDD Cup Competition (John Stamper); (4) Factorization Models for Forecasting Student Performance (Nguyen Thai-Nghe, Tomas Horvath and Lars Schmidt-Thieme); (5) Analyzing Participation of Students in Online Courses Using Social Network Analysis Techniques (Reihaneh Rabbany Khorasgani, Mansoureh Takaffoli and Osmar Zaiane); (6) A Machine Learning Approach for Automatic Student Model Discovery (Nan Li, Noboru Matsuda, William W. Cohen and Kenneth R. Koedinger); (7) Conditions for effectively deriving a Q-Matrix from data with Non-negative Matrix Factorization (Michel C. Desmarais); (8) Student Translations of Natural Language into Logic: The Grade Grinder Translation Corpus Release 1.0 (Dave Barker-Plummer, Richard Cox and Robert Dale); (9) Instructional Factors Analysis: A Cognitive Model For Multiple Instructional Interventions (Min Chi, Kenneth Koedinger, Geoff Gordon, Pamela Jordan and Kurt Vanlehn); (10) The Simple Location Heuristic is Better at Predicting Students Changes in Error Rate Over Time Compared to the Simple Temporal Heuristic (A.F. Nwaigwe and K.R. Koedinger); (11) Items, skills, and transfer models: which really matters for student modeling? (Y. Gong and J.E. Beck); (12) Avoiding Problem Selection Thrashing with Conjunctive Knowledge Tracing (K.R. Koedinger, P.I. Pavlik Jr., J. Stamper, T. Nixon and S. Ritter); (13) Less is More: Improving the Speed and Prediction Power of Knowledge Tracing by Using Less Data (Bahador Nooraei, Zachary Pardos, Neil T. Heffernan and Ryan S.J.D. Baker); (14) Analysing frequent sequential patterns of collaborative learning activity around an interactive tabletop (R. Martinez Maldonado, K. Yacef, Judy Kay, A. Kharrufa and A. Al-Qaraghuli); (15) Acquiring Item Difficulty Estimates: a Collaborative Effort of Data and Judgment (K. Wauters, P. Desmet and W. Van Den Noortgate); (16) Spectral Clustering in Educational Data Mining (Shubhendu Trivedi, Zachary A. Pardos, Gabor Sarkozy and Neil T. Heffernan); (17) Does Time Matter? Modeling the Effect of Time with Bayesian Knowledge Tracing (Yumeng Qiu, Yingmei Qi, Hanyuan Lu, Zachary Pardos and Neil Heffernan); (18) Learning classifiers from a relational database of tutor logs (Jack Mostow, Jose Gonzalez-Brenes and Bao Hong Tan); (19) A Framework for Capturing Distinguishing User Interaction Behaviors in Novel Interfaces (S. Kardan and C. Conati); (20) How to Classify Tutorial Dialogue? Comparing Feature Vectors vs. Sequences (Jose Gonzalez-Brenes, Jack Mostow and Weisi Duan); (21) Automatically Detecting a Students Preparation for Future Learning: Help Use is Key (Ryan S.J.D. Baker, Sujith M. Gowda and Albert T. Corbett); (22) Ensembling Predictions of Student Post-Test Scores for an Intelligent Tutoring System (Zachary A. Pardos, Sujith M. Gowda, Ryan S.J.D. Baker and Neil T. Heffernan); (23) Improving Models of Slipping, Guessing, and Moment-By-Moment Learning with Estimates of Skill Difficulty (Sujith M. Gowda, Jonathan P. Rowe, Ryan S.J.D. Baker, Min Chi and Kenneth R. Koedinger); (24) A Method for Finding Prerequisites Within a Curriculum (Annalies Vuong, Tristan Nixon and Brendon Towle); (25) Estimating Prerequisite Structure From Noisy Data (Emma Brunskill); (26) What can closed sets of students and their marks say? (Dmitry Ignatov, Serafima Mamedova, Nikita Romashkin, and Ivan Shamshurin); (27) How university entrants are choosing their department? Mining of university admission process with FCA taxonomies (Nikita Romashkin, Dmitry Ignatov and Elena Kolotova); (28) What's an Expert? Using learning analytics to identify emergent markers of expertise through automated speech, sentiment and sketch analysis (Marcelo Worsley and Paulo Blikstein); (29) Using Logistic Regression to Trace Multiple Subskills in a Dynamic Bayes Net (Yanbo Xu and Jack Mostow); (30) Monitoring Learners Proficiency: Weight Adaptation in the Elo Rating System (K. Wauters, P. Desmet and W. Van Den Noortgate); (31) Modeling students activity in online discussion forums: a strategy based on time series and agglomerative hierarchical clustering (G. Cobo, D. Garcia, E. Santamaria, J.A. Moran, J. Melenchon and C. Monzo); (32) Prediction of Perceived Disorientation in Online Learning Environment with Random Forest Regression (Gokhan Akcapinar, Erdal Cosgun and Arif Altun); (33) Analysing Student Spatial Deployment in a Computer Laboratory (Vladimir Ivancevic, Milan Celikovic and Ivan Lukovic); (34) Predicting School Failure Using Data Mining (C. Marquez-Vera, C. Romero and S. Ventura); (35) A Dynamical System Model of Microgenetic Changes in Performance, Efficacy, Strategy Use and Value during Vocabulary Learning (P. Pavlik Jr. and S. Wu); (36) Desperately Seeking Subscripts: Towards Automated Model Parameterization (J. Mostow, Y. Xu and M. Munna); (37) Automatic Generation of Proof Problems in Deductive Logic (B. Mostafavi, T. Barnes and M. Croy); (38) Comparison of Traditional Assessment with Dynamic Testing in a Tutoring System (Mingyu Feng, Neil T. Heffernan, Zachary A. Pardos and Cristina Heffernan); (39) Evaluating a Bayesian Student Model of Decimal Misconceptions (G. Goguadze, S. Sosnovsky, S. Isotani and B. Mclaren); (40) Exploring user data from a game-like math tutor: a case study in causal modeling (D. Rai and J. E. Beck); (41) Goal Orientation and Changes of Carelessness over Consecutive Trials in Science Inquiry (A. Hershkovitz, R.S.J.D. Baker, J. Gobert and M. Wixon); (42) Towards improvements on domain-independent measurements for collaborative assessment (Antonio R. Anaya and Jesus G. Boticario); (43) A Java desktop tool for mining Moodle data (R. Pedraza-Perez, C. Romero and S. Ventura); (44) Using data mining in a recommender system to search for learning objects in repositories (A. Zapata-Gonzalez, V.H. Menendez, M.E. Prieto-Mendez and C. Romero); (45) E-learning Web Miner: A data mining application to help instructors involved in virtual courses (Diego Garcia-Saiz and M.E. Zorrilla Pantaleon); (46) Computerized Coding System for Life Narratives to Assess Students' Personality Adaption (Q. He, B.P. Veldkamp and G.J. Westerhof); (47) Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System (Emma Brunskill and Stuart Russell); (48) Mining Teaching Behaviors from Pedagogical Surveys (J. Barracosa and C. Antunes); (49) Variable Construction and Causal Modeling of Online Education Messaging Data: Initial Results (S. Fancsali); (50) The Hospital Classrooms Environments Challenge (Carina Gonzalez and Pedro A. Toledo); (51) Combining study of complex network and text mining analysis to understand growth mechanism of communities on SNS (Osamu Yamakawa, Takahiro Tagawa, Hitoshi Inoue, Koichi Yastake and Takahiro Sumiya); (52) Logistic Regression in a Dynamic Bayes Net Models Multiple Subskills Better! (Yanbo Xu and Jack Mostow); (53) Studying problem-solving strategies in the early stages of learning programming (E. Cambranes-Martinez and J. Good); (54) Brick: Mining Pedagogically Interesting Sequential Patterns (Anjo Anjewierden, Hannie Gijlers, Nadira Saab and Robert De Hoog); (55) Intelligent evaluation of social knowledge building using conceptual maps with MLN (L. Moreno, C.S. Gonzalez, R. Estevez and B. Popescu); (56) Identifying Influence Factors on Students Success by Subgroup Discovery (F. Lemmerich, M. Ifland and F. Puppe); (57) Analyzing University Data for Determining Student Profiles and Predicting Performance (D. Kabakchieva, K. Stefanova and V. Kisimov); (58) The EDM Vis Tool (Matthew Johnson, Michael Eagle, Leena Joseph and Tiffany Barnes); (59) Towards Modeling Forgetting and Relearning in ITS: Preliminary Analysis of ARRS Data (Y. Wang and N.T. Heffernan); (60) Quality Control and Data Mining Techniques Applied to Monitoring Scaled Scores (A.A. Von Davier); (61) eLAT: An Exploratory Learning Analytics Tool for Reflection and Iterative Improvement of Technology Enhanced Learning (A.L. Dyckhoff, D. Zielke, M.A. Chatti and U. Schroeder); (62) Predicting graduate-level performance from undergraduate achievements (J. Zimmermann, K.H. Brodersen, J.-P. Pellet, E. August and J.M. Buhmann); (63) Mining Assessment and Teaching Evaluation Data of Regular and Advanced Stream Students (Irena Koprinska); (64) Investigating Usage of Resources in LMS with Specific Association Rules (A. Merceron); (65) Towards Parameter-Free Data Mining: Mining Educational Data with "yacaree" (Jose L. Balcazar, Diego Garcia-Saiz and Marta E. Zorrilla); (66) Factors Impacting Novice Code Comprehension in a Tutor for Introductory Computer Science (Leigh Ann Sudol-DeLyser and Jonathan Steinhart); (67) Investigating the Transitions between Learning and Non-learning Activities as Students Learn Online (P.S. Inventado, R. Legaspi, M. Suarez and M. Numao); (68) Learning parameters for a knowledge diagnostic tools in orthopedic surgery (S. Lalle and V. Luengo); (69) Problem Response Theory and its Application for Tutoring (P. Jarusek and R. Pelanek); and (70) Towards Better Understanding of Transfer in Cognitive Models of Practice (Michael V. Yudelson, Philip I. Pavlik, Jr. and Kenneth R. Koedinger). Individual papers contain tables, figures, footnotes and references.

Computer gameplay and social media are the two most common forms of entertainment in the digital age. Many scholars share the assumption that leisure-time digital consumption is associated with CS affinity, but there is a dearth of research evidence for this relationship. Female students generally spend less time on gaming and more time on social media than do male students, so a gender comparison perspective is helpful. Using a national sample of 10,197 U.S. college students in introductory CS courses, we found that frequent computer gameplay was strongly associated with CS career interest for both male and female students. However, increased social media use predicted a higher CS career interest for female students, but a lower interest in male students.

In the past eleven years we have developed several papers for ASCUE about hybrid classes. The initial paper we shared our experience developing a hybrid course and followed with comparisons of student opinions about face-to-face, hybrid, and online classes and finally a paper reviewing components that we were using in hybrid and online classes. It has been eight years since we last addressed the topic, in that time, we have gone from using no online classes and limited use of hybrid courses to relying on their availability in order to deliver our BS program in Computer and Information Technology (CIT) to three sites in Purdue Polytechnic statewide locations. In this paper we would like to take a look at where we have come in the last eleven years. We also would like to compare the methods of instruction: face-to-face, hybrid, and online, is one method more successful than others, how do students feel about the methods of instruction? We know the students are unique and those different types of course delivery may appeal to different people. With that in mind, we will look into the students who prefer which environment and why. Finally, if you are teaching a hybrid or online class what can be done in the classroom to be successful. [For the full proceedings, see ED596991.]

"Proceedings of International Conference on Research in Education and Science" includes full papers presented at the International Conference on Research in Education and Science (ICRES) which took place on March 24-27, 2022 in Antalya, Turkey. The aim of the conference is to offer opportunities to share ideas, to discuss theoretical and practical issues and to connect with the leaders in the fields of education and science. The conference is organized annually by the International Society for Technology, Education, and Science (ISTES). The ICRES invites submissions which address the theory, research or applications in all disciplines of education and science. The ICRES is organized for: faculty members in all disciplines of education and science, graduate students, K-12 administrators, teachers, principals and all interested in education and science. After peer-reviewing process, all full papers are published in the Conference Proceedings. [Individual papers are indexed in ERIC.]

COVID-19 presented a challenge to the traditional methods of teaching programming and robotics in a secondary school environment. When campuses were closed around the world in the spring of 2020, it was not possible for students to access the computer labs nor the robotics equipment that was traditionally used to facilitate the instruction of robotics programming units. This paper presents a design research project in which two secondary institutions in Canada and Turkey collaborated to teach computer science and robotics programming, specifically reinforcement learning, through the use of an online simulation environment. The two student cohorts in the study both were successful in developing reinforcement learning models for autonomous vehicles, despite not having any prior experience in machine learning nor artificial intelligence. The implications of this work are that physical robotics kits and dedicated robotics spaces are not essential to the teaching of programming and robotics. This is especially relevant to marginalized communities that do not have the resources to support robotics instruction, further exacerbating the digital divide.

This collection of conference presentations includes 23 papers on a variety of topics pertaining to the use of computer in New Zealand. Among the topics discussed are computer science techniques in a commercial data processing situation, data processing personnel and their careers, the communication aspects of an airline system, implementation of Alsol-W programming systems, computer communications and the fire service, observations on user/vendor communications, future database and application development techniques, system control via a high level language, the organization and management of systems development, and human communication between educational data processors and those outside the profession, e.g., the users. (JEG)

AFTHER, a computer simulation game for dealing with the complexities of higher education in a changing electronic world, is described. It is a tool for decision research and decision assistance. AFTHER enables the users to study higher education governance and its decision-making patterns in general, or to readily convert the simulation to an institution's particular characteristics and problems. This individualized conversion, used for teaching, decision research, or decision assistance, can be done without knowledge of computer language. Within the parameters of the game model, the computer can reprogram itself in all areas and dimensions of analysis and readily accept modified or revised data for institutional analysis. The simulation procedure, simulation elements, advantageous features, and research and development implications are detailed. (Author/MSE)

Thirteen papers from the University of South Africa's Conference on Distance Education are presented on media and technology. They include: "Making the Abstract Concrete: A Slide/Sound Programme to Illustrate Abstract Concepts on the Concrete Level" (Grace Reeler); "The Microcomputer and Distance Education" (Johanna S. Rossouw); "A Multimedia Approach to Creating Learning Experiences in Distance Education" (Louis J. van Niekerk); "The Training of Teachers by Means of Teletuition: The Audio Cassette and Teaching Practice" (Lawrie McFarlane); "Microteaching and Distance Education--The Self Teaching Experience" (Paul J.N. Steyn); "Written Language as Didactic Medium: From Principle to Technology" (Hannes van Deventer); "Computer-Aided Instruction in Quantitative Management--Part 1" (Ilze Olivier et al.); "Computer-Aided Instruction in Quantitative Management--Part 2" (Erica Ferreira, Gordon Erens); "The Application of Computer Technology in Offering Equal Education Opportunities to Students from First- and Third-World Environments" (J. Dewald Lubbe); "The Law Student and the Law Library" (Jean Burdzik); "The Effect of Advances in Information Technology on the Teaching of Practical Aspects in Computer Science at UNISA" (C.H. Bornman et al.); "Die Gebruik van Inligtingstegnologie in Afstandsonderrig" (N.F. du Plooy et al.); and "Computer-Aided Education as Student Centred Education: Practical Applications for Today and the Future" (P.J. van Dyk). (LB)

This paper aims to propose a framework to improve the quality in teaching and learning in order to develop good practices to train professionals in the career of computer engineering science. To demonstrate the progress and achievements, our work is based on two principles for the formation of professionals, one based on the model of learning skills and the second on the model of convergence in information technology and communication (ICT) (Bradley, 2005). In this paper, the results are the validation of the graduation profile as part of the process of self-assessment and the internal strategies of the learning community that allowed to achieve the career validation for five years (2015-2020). [For full proceedings, see ED571459.]

In various fields of computer science the word meaning has been explored. In various fields such as Smart Environment, Distributed Computing and Contextual Consciousness, context conscious devices are in popularity. Context Aware System is the new path towards the technology in Mobile Computing. This is a portable computing component where mobile apps can detect spatial data (e.g. User Place, Period of Day, nearby people, locations and user activities). Now in the era of Mobile Computing, recently we have seen the new developments in Apple iPhone-5 and Samsung Galaxy Note where they have application of Context aware System but it is not that what we call a "Killer App". Context conscious System is an old field but a rich field of research. In this paper, the difficulties and possible solutions are discussed which can serve as guidance to the developer or a researcher hoping to make an efficient Context Aware System a reality. [ABSTRACT FROM AUTHOR]

At present, in the literature that is are devoted to social life, it has become commonplace to claim that we live in the era of the "digital revolution". Our paper deals with computer science in the period from the late 40's to early 60's of the twentieth century, which is considered from the point of view of "intellectual history". We concern ourselves with, in the main, two problems. First is self-consciousness of members of the computer science community in relation to other spheres of scientific and engineering-practical activity, including the question about the correlation of theoretical and applied components in the structure of the knowledge. Secondly, we tell about interactions of a new sphere of professional activity have been occurred in this period with various social practices - scientific, industrial, political and so on. Based on the texts that reflect the incipience of computer science in the West and in the Soviet Union, we reveal some features of the "philosophy" of the early period of the digital revolution in the context of the existence of two ideological systems. [For "NORDSCI International Conference Proceedings: Education and Language Edition (Helsinki, Finland, July 17, 2018). Book 1. Volume 1," see ED603189.]

The author has attended and presented at most ASCUE meetings since 1994, and has worked professionally in research and development, industry, military, government, business, and private and public academia--moving between computer science, software engineering, and business fields at both the undergraduate and graduate level, and even running academic computing for a few years. This paper/session will present/discuss definitions, implications, and relationships of and between the areas of computer science, software engineering, information technology, and business information systems. Included will be perspectives of the history of the past, specific needs of the present, and general directions and predictions of the future, and the implications to academia, business, and other areas. [For the full proceedings, see ED575713.]

Bitcoin in the last decade, has become increasingly popular as a form of electronic currency. This paper aims to review the status and visual map position of research in the internationally Bitcoin studies indexed Scopus that used a bibliometric positioning overview. The research was carried out using bibliometric techniques. Data analysis as well as visualization utilizing VOS Viewer program and the Scopus function for analyze search results. In this review, the details collected applied to 3,281 documents issued from 2011 through 2019. The study reveals that Bouri, E. and Chinese Academy of Sciences, Studies were the most active individual scientists and affiliated institutions in Bitcoin studies. In bitcoin studies, the Computer Science and Lecture Notes in Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics were the most areas of study and dissemination sources. There were one worldwide group maps with collaborative researchers. In order to identify the body of knowledge created from eight years of publication, this study constructed a convergence axis grouping comprising of bitcoin studies: Bitcoin, E-Finance, Blockchain, Privacy, Cybercrime, Computation, and Systems, abbreviated as the theme BFBPCCS. [ABSTRACT FROM AUTHOR]

In this paper, we report on a series of research projects that together motivate a larger idea: the design of lightweight, scalable, and relational learning experiences for overcoming system-level challenges in education. We start by discussing Exploratory Reading Groups, a program designed to expose students to the creative aspects of computer science and to enhance intrinsic motivation and purpose for learning through exploratory reading of research papers. Unlike traditional graduate student reading groups which focus on depth, our reading groups are designed for a broad exploration of ideas. More importantly for this paper, they are designed to be lightweight in time commitment, to be scalable and student-driven, and to foster supportive peer relationships. As we ran this program, we found that these design parameters not only led to our original goal of supporting creative exploration, but also resulted in the unexpected emergent benefit of facilitating student entry into undergraduate research experiences. There were three reasons for this. First, the lightweight nature of the program (~1-2 hours a week for 4 weeks) lowered entry barriers for busy students. Second, the scalable and student-driven nature of the program circumvented the obstacles of limited faculty time or staff resources common to many programs. Third, the relational nature of the program facilitated knowledge sharing and relational networks that helped to overcome the many systemic misalignments at the root of faculty-perceived barriers to undergraduate research, findings that came out of a series of interviews we conducted with STEM faculty on barriers to undergraduate research. We conclude by proposing that the design of lightweight, scalable, and relational learning experiences may be an effective approach to overcoming system-level challenges in education and discuss a few examples of what that might look like and future directions. [ABSTRACT FROM AUTHOR]

Due to increasing digitization in all aspects of life, the demand for qualified software development professionals continues to increase. Students from underrepresented groups, such as first generation students from non-academic families, minorities, single parents and women represent an underutilized pool of untapped potential talent. The question arises as to which unique perspectives computer science graduates from underrepresented groups can bring to software development companies. In addition to programming skills, non-technical competencies, such as foreign language abilities, intercultural communication, creativity, conflict management, team-building and organizational skills are vital for success in diverse, international project teams. A large job market database for new graduates, developed for a consortium of universities in Bavaria, Germany, is analyzed using machine learning tools. Career competencies desired by recruiting companies are compared to potential advantages offered by computer science graduates from underrepresented groups. [For the complete proceedings, see ED608557.]

The "doer effect" is the assertion that the amount of interactive practice activity a student engages in is much more predictive of learning than the amount of passive reading or watching video the same student engages in. Although the evidence for a doer effect is now substantial, the evidence for a causal doer effect is not as well developed. To address this, we mined data for evidence of a causal doer effect across multiple domains. We examined data from two online courses in Psychology, one in Biology, one in Statistics, and two in Information Science, applying causal discovery algorithms in Tetrad to each. Assuming that factors driving a student's choices regarding how to spend their time in an online course are temporally prior to their performance on quizzes and exams, we found evidence of a causal relationship in every domain we studied. We did not find evidence that a unique causal model held in every domain we studied, but when we estimated the size of the causal relationships in the models we found in each domain, we did find evidence in every case that doing has a much stronger quantitative effect on learning than either reading or watching video. This work may be the first EDM effort to explore the generalizability of a causal claim about learning across multiple datasets from a variety of courses and contexts of use. It makes vivid the role of causal data mining algorithms in educational research. The evidence presented furthers the case for doer effect causality, but also recommends a need for richer data with more student background and learning process variables to better isolate causal directionality without assumptions about temporal order and unmeasured confounds. [For the full proceedings, see ED593090.]

Increasing participation and continued persistence of women in computing is a perennial problem. This paper explores how participation in computing has been defined and the consequences definitions have on understanding women's persistence in computing. The data for this paper come from 64 in-depth, qualitative interviews with young women who in high school expressed interest in computing by looking into NCWIT's Aspirations in Computing Award. Drawing on communities of practice as a conceptual framework, analyses of the interviews show that defining participation in computing as engaging in computational thinking unduly prohibits some women from full membership in computing communities. Findings show that some women who self-identify with the computing community are not fully recognized by other members of the computing community.

Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate different methods of following the development of student behaviour throughout the semester using online submission system data, and different approaches to analysing this development. We demonstrate the application of these methods to data from a junior computer science course (N=494) and discuss their usefulness in understanding the common behavioural strategies of students in this course and how these develop over time. Finally, we draw links between behaviour in weekly coding tasks and student performance in the final exam and discuss whether these methods could be applicable midway through the semester. [For the full proceedings, see ED592609.]

Making construals is a practical approach to computing that was originally developed for and by computer science undergraduates. It is the central theme of an EU project aimed at disseminating the relevant principles to a broader audience. This involves bringing together technical experts in making construals and international experts in educational technology in organising wide-ranging learning activities. This paper, which complements the tutorial and discussion on making construals in (Beynon et al. 2015a, 2015b), documents issues that arise from this encounter. Its central argument is that making construals offers a significant new contribution to educational technology. [For the full proceedings, see ED562093.]

A quality educational experience for secondary students involves more than an acquisition of content knowledge; it entails providing students opportunities to develop a variety of thinking skills that enable integration of knowledge and the promotion of student self-directed learning outside of the classroom. One critical skill that is often underemphasized in education is computational thinking. The purpose of this conceptual paper is to discuss the parallels between the processes of computational thinking and self-regulated learning, and the corresponding implications of this integrated framework for instruction in secondary classrooms. Guiding our analysis is the premise that because computational thinking processes can be viewed as goal-directed processes, it is possible to use self-regulated learning theory as a framework for assessing and enhancing computational thinking. Secondary educators have minimal experience with teaching computational thinking in the United States, so not only is a clear definition of computational thinking necessary in the Next Generation Science Standards, it is also necessary to have a learning theory from which to structure this type of thinking. [For the full proceedings, see ED562093.]

The theme of 'embodiment' has become an important approach in current mathematics education research, growing in significance from the mid-1990s onward. However terminology of 'body' and 'embodiment' is used to signal multiple, widely varying meanings in this research. Studies are grounded in a number of radically different theoretical bases, with the result that mathematics education researchers do not necessarily mean the same thing at all when they refer to 'body', 'embodiment' and 'embodied mathematics learning'. In this theoretical paper, the author offers a framework for interpreting these polysemous terms in relation to their theoretical groundings, with examples from the mathematics education literature. [For the complete proceedings, see ED597799.]

Working scientifically and writing a conference paper is usually part of PhD programs, but not part of a regular study program for an undergraduate or master's degree. In a master's degree class for computer science, a concept to combine scientific work with project-based learning was developed and has been carried out twice. The students had to learn the professional skills of the subject social network analysis and gained methodological skills. They had to conduct a research project and to write a conference paper. In the course evaluation, the students state their high learning outcomes, but also they find that the projects are a lot of work and they describe their difficulties with this kind of work. They are used to writing project reports and bachelor's theses, but not to writing conference papers. Therefore, this concept was professionally and methodologically a new and beneficial experience for them. [ABSTRACT FROM AUTHOR]

Improper Input Validation (IIV) is a software vulnerability that occurs when a system does not safely handle input data. Even though IIV is easy to detect and fix, it still commonly happens in practice. In this paper, we study to what extent developers can detect IIV and investigate underlying reasons. This knowledge is essential to better understand how to support developers in creating secure software systems. We conduct an online experiment with 146 participants, of which 105 report at least three years of professional software development experience. Our results show that the existence of a visible attack scenario facilitates the detection of IIV vulnerabilities and that a significant portion of developers who did not find the vulnerability initially could identify it when warned about its existence. Yet, a total of 60 participants could not detect the vulnerability even after the warning. Other factors, such as the frequency with which the participants perform code reviews, influence the detection of IIV. [ABSTRACT FROM AUTHOR]

The study on artificial intelligence (AI) is highly interdisplinary, which involves increasing number of researchers from different academic fields. In order to provide an overview for the researchers on recent publications in related fields, we conducted a statistic analysis using bibliometric methods. Using the data source from Web of Science (ISI), we have studied the articles published in the SCI and SSCI journals on the the subject of AI between the year of 2000 and 2011. The data were analyzed from six aspects, including article distribution by years, journals, languages, countries/regions, research fields, and authors. The result revealed the most influential journals, language and authors in this field, which could help researchers from the related area to find useful in formations and direct their researches. [ABSTRACT FROM PUBLISHER]

The gender gap in computer science is worst amongst any of the STEM fields. At the secondary school level, only 18.6% of AP computer science test-takers in the United States were girls. In order to address the persistent gender gaps in computer science, it is important to understand K-12 students' views about computer science and programming. The present study examined middle school students' perceptions and affective attitudes towards programming. Results suggested that male students were more likely than their female peers to view programming as being interesting and easier to learn. Male students were also significantly more likely to feel that programming was an exciting and relaxing enterprise. We discuss the implications of these findings for computer science in schools.

In response to the glaring disparities in the number of African-Americans, Hispanics, Native Americans, and females employed in computer science (CS) field, the purpose of this study was to enhance underrepresented minority (URM) students' identification with and motivation for CS through a culturally relevant intervention in a required high school mathematics course. This intervention weaved geometry concepts, cultural art, and coding through the virtual presentation of Native American Star Quilts in Python. Participants were 142 high school students across six 10th-grade geometry classes. Three of the six geometry classes were randomly assigned to receive the intervention. Results indicated that the intervention had a positive effect on the development of computer science-oriented possible selves, especially among females, and a positive effect on the CS self-efficacy of females and Hispanic students.