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For the thirty-sixth year, 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 Anaheim, California. The Proceedings of AECT's Convention are published in two volumes. Volume 1 contains papers dealing primarily with research and development topics. Papers dealing with the practice of instructional technology including instruction and training issues are contained in Volume 2. (Individual papers contain references.) [For Volume 2, see ED546878.]

This paper provides a synthesis of the literature on the role of benchmarking, with a focus on its use in the public sector. Benchmarking is discussed in the context of quality systems, of which it is an important component. The paper describes the basic types of benchmarking, pertinent research about its application in the public sector, the purposes of performance indicators, and the types of information such indicators provide. Finally, a benchmarking framework used by the New South Wales Department of School Education in its quality-assurance program is described. Benchmarking provides the conceptual framework that integrates best practice and performance indicators, a vital component of the quality-assurance system. One figure and two tables are included. (LMI)

This paper presents data from a 1989 survey of 48 state higher education executive officers regarding the use of fiscal enhancement programs as a strategy to influence higher education performance. The paper reports on the purposes and objectives most often funded through specific incentives, and on the key advantages and disadvantages of this budget tool. Guidelines for structuring or evaluating such programs are suggested. It was found that 32 states had established enhancement programs which could be classified as categorical programs, competitive programs, or incentive programs. While overall budget conditions have led to reduced dollars being channeled to campuses through enhancement programs, the number of programs and the degree of commitment on the part of states to use enhancement funding techniques is increasing. The purposes most often served by incentive programs were economic growth, technology transfer, and applied research. Advantages of the use of enhancement programs are that they make state policy concrete through the mechanism of the budget, are based on performance indicators, reward and encourage meaningful institutional differentiation, and work as change strategies. Among disadvantages are that these programs emphasize short-term goals over long-term planning and distract public attention away from the necessity to adequately fund the base budget. A postscript discusses the formative and summative uses of incentive program results. (16 references) (JDD)

Simulation--here defined as a physical, procedural, or symbolic representation of certain aspects of a functioning system, or as a working model or representation of a real world system--has at least four areas of application: (1) training where the objective of simulation is to provide the trainee with a learning environment that will facilitate the acquisition of a skill or body of knowledge, (2) performance measurement in the determination of limits of proficiency, research requirements, or training needs, (3) system evaluation in terms of operating objectives, and (4) research where it is important to control and examine certain aspects of the environment. Among the reasons for using simulation techniques rather than other methodologies are: expense and time; safety; ethical or political constraints; past, future, or hypothetical events; and control over real-world events. Several advantages of simulation over other methodologies for training, evaluation, and research are presented together with a conceptual framework for assessing the utility of its application to specific problems. Miniaturization, as a special form of simulation, is described with reference to two military training situations--aircraft identification and marksmanship practice. Some areas needing further research are also presented. (DGC)

The current study examined the influences of SRL prompts provided in three different phases (i.e., forethought, performance, and self-reflection) on college students' learning outcome and SRL levels during video-based learning. Fifty-eight participants were randomly assigned into one of the four conditions: 1) SRL prompts at the forethought phase; 2) SRL prompts at the performance phase; 3) SRL prompts at the self-reflection phase; 4) no SRL prompts in any phase. Participants responded to a questionnaire assessing their self-regulated learning levels and learning outcome after the video. SRL levels were also inferred by learners' behavior of pausing and rewinding during video-watching. Results indicated that participants who received SRL prompts at the performance phase achieved better learning outcomes than those receiving no prompts.

These proceedings contain the papers of the IADIS International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2013), October 22-24, 2013, which has been organized by the International Association for Development of the Information Society (IADIS), co-organized by The University of North Texas (UNT), sponsored by the Association for Educational Communication and Technologies (AECT), and endorsed by the Japanese Society for Information and Systems in Education (JSISE). The CELDA 2013 conference aims to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There have been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a fast pace and affecting academia and professional practice in many ways. Paradigms such as just-in-time learning, constructivism, student-centered learning, and collaborative approaches have emerged and are being supported by technological advancements such as simulations, virtual reality, and multi-agents systems. These developments have created both opportunities and areas of serious concerns. This conference aims to cover both technological as well as pedagogical issues related to these developments. However, innovative contributions that do not easily fit into these areas are also included as long as they are directly related to the overall theme of the conference--cognition and exploratory learning in the digital age. The conference included the Keynote Lecture: "Ubiquitous Learning Analytics for Adaptive and Authentic Instruction," by Professor Kinshuk, Associate Dean of Faculty of Science and Technology, NSERC/iCORE/Xerox/Markin Industrial Research Chair--School of Computing and Information Systems, Athabasca University, Canada. The conference also included a panel entitled "Interactive Technologies for Teacher Training: Two Technology Approaches and Their Implications," with Julia Meritt, David Gibson, Rhonda Christensen, Gerald Knezek, and Wilhelmina Savenye. Papers presented in this conference include: (1) Working Memory Intervention: A Reading Comprehension Approach (Tracy L. Perry and Evguenia Malaia); (2) Suggestions for the Design of E-Learning Environments to Enhance Learner Self-Efficacy (Charles B. Hodges); (3) Student and Teacher Use of Technology at the University Level (Peter Gobel and Makimi Kano); (4) Understanding and Applying Technology in Faculty Development Programs (Sharon L. Burton and Dustin Bessette); (5) Measuring Problem Solving Skills in "Portal 2" (Valerie J. Shute and Lubin Wang); (6) Students' Facebook Usage and Academic Achievement: A Case Study of Private University in Thailand (Wilailuk Sereetrakul); (7) Students' Usage of Facebook for Academic Purposes: A Case Study of Public and Private Universities in Thailand (Ampai Thongteeraparp); (8) Persistence of Cognitive Constructs Fostered by Hands-On Science Activities in Middle School Students (Rhonda Christensen, Gerald Knezek, Tandra Tyler-Wood, and David Gibson); (9) Spanning Knowledge Barriers in E-Learning Content Design (Tsai-Hsin Chu, Yi Lee, and Yen-Hsien Lee); (10) ASK LDT 2.0: A Web-Based Graphical Tool for Authoring Learning Designs (Panagiotis Zervas, Konstantinos Fragkos, and Demetrios G. Sampson); (11) Model of Emotional Expressions in Movements (Vladimir L. Rozaliev and Yulia A. Orlova); (12) The ANCESTOR Project: Aboriginal Computer Education through Storytelling (Marla Weston and Dianne Biin); (13) Context-Based Semantic Annotations in CoPEs: An Ontological and Rule-Based Approach (Souâad Boudebza, Lamia Berkani, and Faiçal Azouaou); (14) Mobile Augmented Reality in Supporting Peer Assessment: An Implementation in a Fundamental Design Course (Chung-Hsien Lan, Stefan Chao, Kinshuk, and Kuo-Hung Chao); (15) Intelligent Tutors in Immersive Virtual Environments (Peng Yan, Brian M. Slator, Bradley Vender, Wei Jin, Matti Kariluoma, Otto Borchert, Guy Hokanson, Vaibhav Aggarwal, Bob Cosmano, Kathleen T. Cox, André Pilch, and Andrew Marry); (16) Can Free-Range Students Save Some Schools? A Case Study on a Hybrid Classroom (Christopher Francis White); (17) ICT Support for Collaborative Learning--A Tale of Two Cities (Teresa Consiglio and Gerrit C. van der Veer); (18) Issues of Learning Games: From Virtual to Real (Thibault Carron, Philippe Pernelle, and Stéphane Talbot); (19) Data Challenges of Leveraging a Simulation to Assess Learning (David Gibson and Peter Jakl); (20) Self-Assessment and Reflection in a 1st Semester Course for Software Engineering Students (Jacob Nielsen, Gunver Majgaard, and Erik Sørensen); (21) Journey of Exploration on the Way towards Authentic Learning Environments (Merja Meriläinen and Maarika Piispanen); (22) Supporting the Strengths and Activity of Children with Autism in a Technology-Enhanced Learning Environment (Virpi Vellonen, Eija Kärnä, and Marjo Virnes); (23) Transforming Education in a Primary School: A Case Study (Cathleen A. Norris, Elliot Soloway, Chun Ming Tan, Chee Kit Looi, and Akhlaq Hossain); (24) Using Generic and Context-Specific Scaffolding to Support Authentic Science Inquiry (Brian R. Belland, Jiangyue Gu, Sara Armbrust, and Brant Cook); (25) Using a Facebook Group as a Forum to Distribute, Answer and Discuss Content: Influence on Achievement (Blanche W. O'Bannon, Virginia G. Britt, and Jeffrey L. Beard); (26) Some Psychometric and Design Implications of Game-Based Learning Analytics (David Gibson and Jody Clarke-Midura); (27) Piaget, Inhelder and "Minecraft" (Catherine C. Schifter, Maria Cipollone, and Frederick Moffat); (28) Math on a Sphere: Making Use of Public Displays in Education (Michael Eisenberg, Antranig Basman, and Sherry Hsi); (29) Research on the E-Textbook and E-Schoolbag in China: Constructing an Ecosystem of E-Textbook and E-Schoolbag (Yonghe Wu, Lin Lin, Xiaoling Ma, and Zhiting Zhu); (30) A Study on Improving Information Processing Abilities Based on PBL (Du Gyu Kim and JaeMu Lee); (31) Tablets in the Classroom: Improvisational Rhythms and Change through Bricolage (Bente Meyer); (32) Using REU Projects and Crowdsourcing to Facilitate Learning on Demand (Hong P. Liu and Jerry E. Klein); (33) iPads in Inclusive Classrooms: Ecologies of Learning (Bente Meyer); (34) Designing Learning Object Repositories as Systems for Managing Educational Communities Knowledge (Demetrios G. Sampson and Panagiotis Zervas); (35) The Configuration Process of a Community of Practice in the Collective Text Editor (Cláudia Zank and Patricia Alejandra Behar); (36) Cross-Continental Research Collaborations about Online Teaching (Kevin P. Gosselin and Maria Northcote); (37) Leverage Learning in the University Classroom (Melissa Roberts Becker, Pam Winn, and Susan Erwin); (38) Using Loop Learning and Critical Dialogue in Developing Innovative Literature Reviews (Marilyn K. Simon and Jim Goes); (39) Developing a Connectivist MOOC at a College of Education: Narrative of Disruptive Innovation? (Dalit Levy and Sarah Schrire); (40) The Cognitive Cost of Chatting While Attending a Lecture: A Temporal Analysis (Chris Bigenho, Lin Lin, Caroline Gold, Arjun Gupta, and Lindsay Rawitscher); (41) "Visual Selves": Construction Science Students' Perceptions about Their Abilities to Represent Spatial Related Problems Internally and Externally (Tamera McCuen and Xun Ge); (42) Educational Affordances That Support Development of Innovative Thinking Skills in Large Classes (Julaine Fowlin, Catherine Amelink, and Glenda Scales); (43) Technology and Curriculum Standards: How Well Do Internet-Based Learning Games Support Common Core Standards for Mathematics? (Teri Bingham and Jan Ray); (44) English Proficiency and Participation in Online Discussion for Learning (Steve Leung); (45) Problem-Based Educational Game Becomes Student-Centered Learning Environment (Pornpimon Rodkroh, Praweenya Suwannatthachote, and Wannee Kaemkate); (46) Technology and Cognition Merge with Challenge-Based Learning Cycles Online (Shelley L. Cobbett); (47) Student-Driven Classroom Technologies: Transmedia Navigation and Transformative Communications (Leila A. Mills, Gerald A. Knezek, and Jenny S. Wakefield); (48) The Investigation of Pre-Service Teachers' Concerns about Integrating Web 2.0 Technologies into Instruction (Yungwei Hao, Shiou-ling Wang, Su-jen Chang, Yin-hung Hsu, and Ren-yen Tang); (49) An Examination of Teachers' Integration of Web 2.0 Technologies in Secondary Classrooms: A Phenomenological Study (Ling Wang); (50) Perceived Affordances of a Technology-Enhanced Active Learning Classroom in Promoting Collaborative Problem Solving (Xun Ge, Yu Jin Yang, Lihui Liao, and Erin G. Wolfe); (51) Authentic Learning through GBL: Using Inquiry and PBL Strategies to Accomplish Specific Learning Outcomes through Smart Games in Formal and Informal Settings (Brad Hoge); (52) Dealing with Unseen Obstacles to Education in the Digital Age (Valerie J. H. Powell, Arif Sirinterlikci, Christopher Zomp, Randall S. Johnson, Phillip Miller, and James C. Powell); (53) Implementing Collaborative Design in the Next Series of eLearning Platforms (Dorothy Kropf); (54) Facing the Challenge--Developing an Instructional Plan for Portuguese as Foreign Language in Brazil Based on Multiliteracy (Ana Flora Schlindwein); (55) Life-Long Learning and Social Responsibility Obligations (Robin Mayes); (56) The Contributions of Digital Concept Maps to Assessment for Learning Practices (Mehmet Filiz, David Trumpower, and Sait Atas); (57) Don't Waste Student Work: Using Classroom Assignments to Contribute to Online Resources (Jim Davies); (58) Leveraging Sociocultural Theory to Create a Mentorship Program for Doctoral Students (Matt Crosslin, Jenny S. Wakefield, Phyllis Bennette, and James William Black, III); (59) Demonstrable Competence: An Assessment Method for Competency Domains in Learning and Leadership Doctoral Program (David W. Rausch and Elizabeth K. Crawford); (60) Confidence-Based Assessments within an Adult Learning Environment (Paul Novacek); (61) Effect of Digitally-Inspired Instruction on Seventh Grade Science Achievement (Pam Winn, Susan Erwin, Melissa Becker, and Misty White); (62) Interactive Technologies for Teacher Training: Comparing Performance and Assessment in Second Life and SimSchool (Julia Meritt, David Gibson, Rhonda Christensen, and Gerald Knezek); (63) Some Considerations on Digital Reading (Rodrigo Esteves de Lima-Lopes); (64) An Alternative Approach to Test Analysis and Interpretation (J. C. Powell); (65) Volition Support Design Model (ChanMin Kim); (66) Tekking: Transversing Virtual and International Boundaries to Explore and Develop Effective Adult Learner Experiences (Ruth Gannon Cook); (67) Strengthening Parent-Child Relationships through Co-Playing Video Games (Anneliese Sheffield and Lin Lin); and (68) Reflection Paper on a Ubiquitous English Vocabulary Learning System: Evidence of Active/Passive Attitude vs. Usefulness/Ease-of-Use (Jeff Lim). An author index is included. Individual papers contain references. Luís Rodrigues is the associate editor of these proceedings.

The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for amplifying human potential." Not all students or seekers of knowledge receive the education necessary to help them realize their full potential, be it due to a lack of resources or lack of access to high quality teaching. The dearth in high-quality educational content, teaching aids, and methodologies, and non-availability of objective feedback on how they could become better teachers, deprive our teachers from achieving their full potential. The administrators and policy makers lack tools for making optimal decisions such as optimal class sizes, class composition, and course sequencing. All these handicap the nations, particularly the economically emergent ones, who recognize the centrality of education for their growth. EDM-2023 has striven to focus on concepts, principles, and techniques mined from educational data for amplifying the potential of all the stakeholders in the education system. The spotlights of EDM-2023 include: (1) Five keynote talks by outstanding researchers of eminence; (2) A plenary Test of Time award talk and a Banquet talk; (3) Five tutorials (foundational as well as advanced); (4) Four thought provoking panels on contemporary themes; (5) Peer reviewed technical paper and poster presentations; (6) Doctoral students consortium; and (7) An enchanting cultural programme. [Individual papers are indexed in ERIC.]

An extended (and probably unnecessary) parallel is drawn between engagement in mathematics and engagement in musical performance. Key facets of engagement are described and a model of how mathematics engagement plays out in task-level activities is discussed in light of new findings related to its social and emotional facets. Implications for instructional practices that flow from this research are presented. The article concludes with suggestions for future research that incorporates understandings of identity and emotional object as promising directions. [For the complete proceedings, see ED657822.]

Educational technologies may help support out-of-school learning in contexts where formal schooling fails to reach every child, but children may not persist in using such systems to learn at home. Prior research has developed methods for predicting learner dropout but primarily for adults in formal courses and Massive Open Online Courses (MOOCs), not for children's voluntary ed tech usage. To support early literacy in rural contexts, our research group developed and deployed a phone-based literacy technology with rural families in Côte d'Ivoire in two longitudinal studies. In this paper, we investigate the feasibility of using time-series classification models trained on system log data to predict gaps in children's voluntary usage of our system in both studies. We contribute insights around important features associated with sustained system usage, such as children's patterns of use, performance on the platform, and involvement from other adults in their family. Finally, we contribute design implications for predicting and supporting learners' voluntary, out-of-school usage of mobile learning applications in rural contexts. [This paper was published in: "AIED 2020, LNAI 12163," edited by I. I. Bittencourt et al., Springer Nature Switzerland, 2020, pp. 92-105.]

Reported are the execution and outcomes of the Tennessee Higher Education Commission (THEC) Performance Funding Project at Tennessee Technological University, a pilot project seeking to explore the question of whether it is desirable and possible to allocate state funds to community colleges and universities on a performance effectiveness criterion (how good) as compared to the current credit hour and enrollment criteria (how much). The University project is part of a larger state-wide effort sponsored by the THEC and funded by grants from several sources. This case study presentation is organized according to the following topics: First, the background for the state-level project is discussed as part of the national trend of concern about accountability. Second, the rationale for and objectives of the state-level project are considered. Third, the experiences at Tennessee Technological University are presented, with attention to the participants and to the events and procedures involved in its execution. The first year was dedicated to the development of instructional goals and performance indicators; the second year, with the acquisition of data on these indicators and the development of ways in which performance might be incorporated into the funding project. Positive outcomes are cited and some explanations for the relative degree of success to date are offered. Attention is also given to remaining challenges and problems. (Author/JMD)

Students on many campuses regularly evaluate their courses, and reports of these evaluations are sent to their instructors. Such feedback should result in improved teaching and in more positive evaluations, yet neither informal observation nor systematic studies reveal sizable feedback effects. The true effects of feedback of this kind are modest, and estimates of the true effects are attenuated by design and measurement problems and definition and implementation problems. Three kinds of evidence are described that support this contention: (1) original sin (some faculty deny the value of student ratings and once they have a PhD or get tenure, they no longer are able to distinguish pedagogical truth from pedagogical error); (2) archival data (little evidence of improved ratings over time which would indicate improvement); and (3) controlled studies, design and measurement, generalizing from midterm pretests, measurement scale characteristics, and definition and implementation problems, including definition of feedback, and unstated assumptions). The influence of generalizing from midterm pretests is uncertain. All of the other problems are likely to reduce the chances of identifying feedback effects. Measurement issues make it harder to detect true differences. Diffusion treatment can dilute feedback effects. Failure to verify implementation of treatment and investigate other assumptions about the treatment also attenuate true effects of feedback. Contains 8 references. (SM)

This paper provides a detailed description of how a smart spaces laboratory has been used for assessing learners' performance in various educational contexts. The paper shares the authors' experiences from using sensor-generated data in a number of learning scenarios. In particular the paper describes how a smart learning environment is created with the use of a range of sensors measuring key data from individual learners including (i) heartbeat, (ii) emotion detection, (iii) sweat levels, (iv) voice fluctuations and (v) duration and pattern of contribution via voice recognition. The paper also explains how biometrics are used to assess learner' contribution in certain activities but also to evaluate collaborative learning in student groups. Finally the paper instigates research in the role of using visualization of biometrics as a medium for supporting assessment, facilitating learning processes and enhancing learning experiences. Examples of how learning analytics are created based on biometrics are also provided, resulting from a number of pilot studies that have taken place over the past couple of years. [For the complete proceedings, see ED590269.]

Assessing student presentations can be made more reliable with video-recording and post-performance rating. Further, self assessment and peer assessment can aid in the learning process by students when using specific, easy-to-understand rubrics. A ten-year action research study involved video-recorded performance assessment tasks using a free, open-source Moodle module developed by Sapporo Gakuin University. The Video Assessment Module (VAM) allowed teachers to video record English presentations and upload them to the module for students for self and peer assessment on specific rubrics using qualitative and quantitative criteria. When compared to paper rubrics, the VAM reduced teacher management time and students could use out-of-class time to assess asynchronously without time pressure. Results showed that there was a higher difference in teacher variance for self assessment when compared to teacher variance with peer assessment. Qualitative and quantitative results reported value in using the tool by both students and teachers. This study also showed that students can be trained to use online rubrics to score presentations efficiently, giving further validity for using and developing online modules for video assessment. [For the complete proceedings, see ED600837.]

Personalized education systems recommend learning contents to students based on their capacity to accelerate their learning. This paper proposes a personalized exercise recommendation system for online self-directed learning. We first improve the performance of knowledge tracing models. Existing deep knowledge tracing models, such as Dynamic Key-Value Memory Network (DKVMN), ignore exercises' concept tags, which are usually available in tutoring systems. We modify DKVMN to design its memory structure based on the course's concept list, and explicitly consider the exercise-concept mapping relationship during students' knowledge tracing. We evaluated the model on the 5th grade students' math exercising dataset in TAL, one of the biggest education groups in China, and found that our model has higher performance than existing models. We also enhance the DKVMN model to support more input features and obtain higher performance. Second, we use the model to build a student simulator, and use it to train an exercise recommendation policy with deep reinforcement learning. Experimental results show that our policy achieves better performance than existing heuristic policy in terms of maximizing the students' knowledge level. To the best of our knowledge, this is the first time that deep reinforcement learning has been applied to personalized mathematic exercise recommendation. [For the full proceedings, see ED599096.]

Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the ASSISTment 2009-2010 dataset for n = 4,217 middle-school students in the United States to predict whether a student is wheel-spinning. Although both models yielded high predictive accuracy, bagged trees significantly outperformed decision trees. Results show that (1) a tree-based model is effective at accurately predicting wheel-spinning and (2) students are taking more than the average amount of attempts to master a skill.

This study conducted an exploratory study to compare children's performance on a video game-based task to their performance on an analogous hands-on physical task. The game involved a slide and concepts of height and friction. For both formats, the number of rounds it took to beat a level and the number of steps used within each round were measured. The number of rounds to beat a level between the two modes were not drastically different. However, the number of steps (per round) to beat a round was higher in the game than the hands-on task, suggesting a mode effect. The digital format appeared to be interfering with children's ability to "sense" friction, which was not observed in the hands-on task. [The work reported here was supported by the PBS KIDS Digital.]

Performance prediction has emerged as one of the most popular approaches to leverage large volume of online learning data. In the majority of current works, performance prediction is based on students' past activities in graded learning resources (such as problems and quizzes), while their activities in non-graded resources (such as reading material) are ignored. In this paper, we introduce an approach that can take advantage of students' work with non-graded learning resources, as "auxiliary" data, in order to predict students' performance in graded resources. This approach can discover the hidden inter-relationships between learning resources of different types, only using student activity data. Based on our experiments, the proposed approach can significantly reduce the error of student performance prediction, compared to baseline algorithms, while discovering meaningful and surprising relationships among learning resources. [For the full proceedings, see ED593090.]

"Proceedings of International Conference on Humanities, Social and Education Sciences" includes full papers presented at the International Conference on Humanities, Social and Education Sciences (iHSES) which took place on April 22-25, 2021 in New York, USA-www.ihses.net. 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 humanities, education and social sciences. The conference is organized annually by the International Society for Technology, Education, and Science (ISTES)-www.istes.org. The iHSES invites submissions which address the theory, research or applications in all disciplines of humanities, education and social sciences. The iHSES is organized for: faculty members in all disciplines of humanities, education and social sciences, graduate students, K-12 administrators, teachers, principals and all interested in humanities, education and social sciences. After peer-reviewing process, all full papers are published in the Conference Proceedings.

Simulation-based learning environments have been proposed by researchers, as educational tools to support learning in complex business systems. However, studies have evidenced that subjects may nevertheless have great difficulty understanding and managing dynamic systems. Previous research has revealed positive learning and performance effects of using transparent simulations (that is, revealing users the structure and behaviour of the simulator model). This study explores the effects of combining exploratory guidance, learning goals, and performance goals in a transparent simulation of a dynamically complex system. We present a set of hypotheses about the influence of different goal-setting conditions on participants' performance and comprehension of the system dynamics. In a simulation experiment, participants interacted with a system dynamics model representing the growth of a business venture. Participants who previously worked higher learning goals under exploratory guidance and were then submitted to higher performance goals (compared to vague goals) achieved higher performance and demonstrated better comprehension of the model dynamics. However, participants who were only subjected to more specific, high performance goals (compared to vague performance goals) did not improve their outcomes and revealed larger differences within the treatment group. Two out of the four hypotheses were confirmed. In a transparent simulation of a dynamically complex system, setting specific, high learning goals, previously worked through exploratory guidance, positively moderates the impact of the level of performance goals on the comprehension of the model dynamics and performance. [For the full proceedings, see ED621108.]

We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the state-of-the-art systems in predicting whether or not students will answer a given question correctly. In particular, DPE is unaffected by the cold-start problem which arises when new students come to the system with little to no data available. We also show strong performance of the model when removing students' histories altogether, relying in part on contextual information about the questions. This strong performance without any information about the learners' histories demonstrates the high potential of using deep embedded representations of contextual information in educational data mining. [For the full proceedings, see ED607784.]

Estimating the prerequisite structure of skills is a crucial issue in domain modeling. Students usually learn skills in sequence since the preliminary skills need to be learned prior to the complex skills. The prerequisite relations between skills underlie the design of learning sequence and adaptation strategies for tutoring systems. The prerequisite structures of skills are usually studied by human experts, but they are seldom tested empirically. Due to plenty of educational data available, in this paper, we intend to discover the prerequisite structure of skills from student performance data. However, it is a challenging task since skills are latent variables. Uncertainty exists in inferring student knowledge of skills from performance data. Probabilistic Association Rules Mining proposed by Sun et al. (2010) is a novel technique to discover association rules from uncertain data. In this paper, we preprocess student performance data by an evidence model. Then the probabilistic knowledge states of students estimated by the evidence model are used by the probabilistic association rules mining to discover the prerequisite structure of skills. We adapt our method to the testing data and the log data with different evidence models. One simulated data set and two real data sets are used to validate our method. The discovered prerequisite structures can be provided to assist human experts in domain modeling or to validate the prerequisite structures of skills from human expertise. [For complete proceedings, see ED560503.]

This paper examines the impact of the informational value of feedback choices on students' performance, their choice to revise, and the time they spend designing posters and reading feedback in an assessment game. Choices to seek confirmatory or critical feedback and to revise posters in a poster design task were collected from a hundred and six Grade 8 students from a middle school in California via Posterlet, a computer-based assessment. Results show that critical uninformative feedback is associated with performance, critical informative feedback is associated with students' learning strategies (i.e., willingness to revise and feedback dwell time), while confirmatory informative feedback is negatively associated with performance and learning strategies. This research has implications for designing the informational content of feedback messages to support student performance on an open-ended design task. [For the complete proceedings, see ED579395.]

An overview of an international conference held on the campus of the University of California at Los Angeles (UCLA) to take stock of the development and use of educational quality indicator systems at the local, state, national, and international levels is provided. Major implications and findings of the education summit held at the University of Virginia (Charlottesville), September 27-28, 1989, by President Bush and the nation's governors are discussed in the opening address by Emerson J. Elliott entitled "Accountability in the Post-Charlottesville Era." Educational reform in the area of accountability; indicators used by the National Center on Education Statistics; setting national goals and assigning accountability; measuring processes; and issues related to accountability and indicator systems, i.e., controls, and content, are examined; and an agenda for the future is briefly considered. Following this, summaries of six plenary sessions are provided. Because all groups in the education community must be involved in the dialog about the status and improvement of indicator systems, each panel of speakers included policy makers, practitioners, and researchers. The session topics include: (1) National and State Issues: The Role of NAEP; (2) State and District Issues: The Role of Indicators and Assessment in School Reform and School Restructuring; (3) National and State Issues: The Impact of Commercial Achievement Tests; (4) Performance Assessment: Implications for Large-Scale Assessment and Indicators; (5) Accountability and At-Risk Students; and (6) International Educational Indicators: Their International and National Roles. In conclusion, conference participants' responses to a questionnaire that asked them to specify the benefits and dangers of indicator systems and to identify implications for policy, practice, and research are identify implications for policy, practice, and research are summarized. Sixty-one publications available from the UCLA Center for the Study of Evaluation are listed. (RLC)

Demographic information often proves useful for finding subpopulations in educational data. Unfortunately, it is often not collected in the log files of online learning systems, which serve as one of the primary sources of data for the Educational Data Mining community. Recent work has sought to address this issue by investigating school-level differences in demographics, which can be used to discover trends in data where individual-level variation may be difficult or impossible to acquire. In this study, we use this approach to investigate the effect of demographic patterns on hint usage in an elementary level mathematics system, comparing this use to performance and motivational measures. In doing so, we expand upon the research into help-seeking behaviors, which typically takes a cognitive approach. Our results suggest the need to better understand what social factors are most likely to motivate help-seeking behaviors, particularly since research on their effectiveness has been mixed. [For the full proceedings, see ED599096.]

The Association Supporting Computer Users in Education (ASCUE) is a group of people interested in small college computing issues. It is a blend of people from all over the country who use computers in their teaching, academic support, and administrative support functions. Begun in 1968 as the College and University Eleven-Thirty Users' Group (CUETUG), with an initial membership requirement of sharing at least one piece of software each year with other members, ASCUE has a strong tradition of bringing its members together to pool their resources to help each other. ASCUE continues the tradition of sharing through its national conference held every year in June, its conference proceedings, and its newsletter. ASCUE proudly affirms this tradition in its motto: "Our Third Quarter Century of Resource Sharing." ASCUE initiated a refereed track for paper submissions to the conference in 2008. In fact, at the 2008 business meeting, the membership approved three different presentation tracks: refereed with 3 blind reviews for each paper, session with paper where the author submits a paper but it is not reviewed, and session without paper where no paper is submitted and only the abstract is included in the proceedings. To reflect this division, the proceedings is divided into three sections. The first section, up to page 60, contains the approved refereed papers, the second section, from 61 to 79, holds the papers from the sessions with paper, and the last section lists the abstracts for the other sessions. A presenters index is included.

These proceedings contain the abstracts of papers of EDUSREF 2019, which was held in Ankara, Turkey on 28-29 June 2019. Establishing in 2018 as a scientific initiative; Education, Society & Reform Research (EDUSREF) is an International Conference that aims to bridge the knowledge gap, promote social research esteem, and produce democratic information for potential education reforms. The 2019 conference included five keynote presentations from (1) Mehmet Demirezen, Professor from Ufuk University, on "Pausing as Sustained Juncture in spoken English: Clues for Turkish English Teachers"; (2) Suleyman Sadi Seferoglu, Professor from Hacettepe University, on "Industry 4.0 and Digital Transformation: Education of the Future? or The Future of Education?"; (3) Fatma Mizikaci, Associate Professor from Ankara University, on "Education of the Generation Z: Dilemmas, Challenges, and Opportunities"; (4) Davud William Samuel Peachy, Assistant Professor from Duzce University, on "Learning Versus Teaching: A Real Student Seizes Opportunities and Overcomes Difficulties"; and (5) Saniye Vatansever, Assistant Professor from Bilkent University, on "Gender Equality and Inclusion". The papers presented at the conference include: (1) Visual Interactive Text Books for Millennial in University Education (Arshad Taseen); (2) Another Ethical Dilemma? To Teach or not to Teach Ethics at Tertiary Level (Pinar Ayyildiz and Hasan Serif Baltaci); (3) Opinions of the Students Who Prefer the Department of Arabic Translation and Interpreting Studies at the Faculty of Humanities and Social Sciences of Yildirim Beyazit University in Ankara (Haci Yilmaz); (4) Examining Teacher Candidates' Learning Strategies With Regard To Various Variables (Senol Orakci and Yalcin Dilekli); (5) Investigation of the Individual Innovativeness Levels of Teacher Candidates (Senol Orakci); (6) The Integrating of ICTs in the teaching of the Physical sciences in Morocco: Challenges and Obstacles (Zineb Azar, Oussama Dardary, Malika Tridane, Said Benmokhtar, and Said Belaaouad); (7) The feasibility of applying the Finnish approach in Morocco (Oussama Dardary, Zineb Azar, Malika Tridane, and Said Belaaouad); (8) Impact of New Technologies on the Academic Performance of Students: the Case of Smartphones (Imane Echchafi, M. Talbi, and A. Bahloul); (9) Biology Teacher Candidates' Awareness About Biomimicry (Alev Cakir); (10) Teaching Academic Writing through the Use of Reflections (Mira M Alameddine and Ghada Chihimi); (11) Teaching Academic Writing to English 100 Learners at a Local Lebanese University (Mira M. Alameddine and Ghada Chihimi); (12) Cultural Policy of ELT in Turkey (Omer Gokhan Ulum); (13) Graduate Orphans of ELT Departments: A Critical Inquiry (Omer Gokhan Ulum); (14) Spelling Pronunciation versus Relaxed Pronunciation in Teacher Education (Mehmet Demirezen); (15) Performance-based funding in higher education: A global trend, national forms, complex politics. A four-system analysis (Edmund Adam); (16) New Approaches for Teacher Training and Usage of Information Technology in This Context (Haydar Ates); (17) Questioning of Changes in Education: Looking for Priorities (Mustafa Ozmusul); (18) Animation Based Teaching for Gifted (Efe Biyikli, Ali Berkay Harmanci, Ilkiz Ipek Ayten, and Ahmet Berat Ozturk); Intervention for Intermediate Students to Increase Psychological Engagement (Fatima Z. Allahverdi); (20) The influence of guidance counselor practices on the orientation of high school student (Nawal Chiboub, Malika Tridane, and Said Belaaouad); (21) Towards Re-imagining Anganwadi with and for Adolescent Girls (Sam Jacob); (22) The Social Control in the Government-Run Dormitories in Ankara (Melahat Demirbilek); and (23) Comparing Instructional Differences and Teacher Preparedness and its Effect on Psychological Engagement (Fatima Z. Allahverdi). [Individual abstracts contain references.]

This paper examines the development of international education-policy indicators and some conceptual and methodological issues that shape how cross-national comparisons may be made. During the late 1980s representatives of education ministries and departments of the Organisation for Economic Cooperation and Development (OECD) member states initiated the Indicators of Education Systems Project (INES), the first system of comparative education policy indicators on education. The INES Project represents the single best source of international policy indicators today. The paper identifies issues in comparing states and nations, which include different locuses of policy decision making, variation among the study populations, and different contexts of educational environments. Factor analysis was used to examine the social context of American states and European nation-states with more centralized education policies. The data found a common social context characterized by violent death among youth, youth poverty, and teenage births. The American states were found to be more different than alike on the social context of education, and some eastern states appeared to be more like European countries than other states. The paper recommends that member OECD countries commit to complete reporting of at least the core education indicators. One figure and two tables are included. (Contains 27 references.) (LMI)

This paper examines the role of Big Data Analytics in addressing contemporary challenges associated with current changes in institutions of higher education. The paper first explores the potential of Big Data Analytics to support instructors, students and policy analysts to make better evidence based decisions. Secondly, the paper presents an institutional framework for exploring Big Data at the University of Otago in New Zealand. Thirdly, a series of use-case scenarios are presented to demonstrate the benefits of Big Data in Higher Education, and some of the challenges associated with implementation. Finally the paper concludes by outlining future directions relating to the institutional project on Big Data at the University of Otago. [For full proceedings, see ED557168.]

Many schools and school districts are attempting to introduce principles and practices of Total Quality Management (TQM). These attempts take many forms with varying degrees of commitment of resources and management attention. This paper describes the research design of a study intended to identify best current practices in applying TQM concepts to K-12 school districts across the United States. Specifically, the paper describes the sampling procedure and data obtained in the first phase of selecting schools and districts for later study. A questionnaire sent to a national sample of 205 schools and school districts involved in TQM elicited 43 completed surveys. Three additional respondents sent information (without surveys) and five more respondents participated in telephone interviews. Criteria for inclusion in the study included: (1) involvement of constituents in decision making; (2) a focus on instructional processes; and (3) evidence of data collection and baseline measures. The questionnaire was not seen as powerful enough to determine whether a school was really serious about using TQM to make important changes in teaching and learning so a second level of screening was pursued. Approximately 22 of the responses met the three basic criteria and will be considered for the second level qualification stage consisting of follow-up phone interviews. A set of schools which will become the sites for longitudinal case studies will be selected from this screening. It is argued that TQM has the potential to achieve significant change because the organization uses the results of its evaluation of outcomes and processes to improve practice, and the focus on the client/customer translates into a gain in credibility. One figure and the quality improvement practices survey are included. The initial analysis of survey data from practices in quality improvement in teaching and learning is appended. Contains 21 references. (LMI)

Within the past 5 years there has been an international movement to adapt the principles and practices of Total Quality Management work environments to school-restructuring agendas. This paper reports on the development of a model called the Educational Quality System, a benchmark assessment tool for identifying the essential elements of quality work cultures. In 1994, the Florida Department of Education funded a partnership to develop an education-specific Quality system that would include benchmarks to identify progress over time as education institutions pursue Quality work cultures. The partnership was comprised of the University of South Florida, 13 school districts, and a regional network. The paper addresses the issues observed in managing change, explores the mind shifts necessary for inventing new forms of schooling, and describes the two conceptual models driving the Education Quality System. The information is based on a case study that examined the change process in 28 Florida schools. Data were obtained from interviews with the 28 principals and surveys of 1,235 teachers. The most striking pattern among the principals was that they strongly held visions of success for all students and believed in their faculty's capacity to respond to the needs of students. Two tables and two figures are included. (Contains 21 references.) (LMI)

This paper focuses on the evaluation of the on-the-job performance of school district superintendents as they implement school board policy. It draws from the results of a federally supported project on improvement of administrator performance evaluation. Following an overview of the paper's objectives and rationale, part 1 offers a brief history of the superintendency, its duties, competencies, and requirements. Part 2 presents basic concepts for developing a superintendent performance-evaluation model, outlining tasks in the personnel evaluation process. The main models used to evaluate superintendents' performance are assessed in the third part. Part 4 provides a draft of an improved evaluation model based on communication between the board and administrator and on sound conceptualizations of the superintendent's duties. The final part discusses implementing the model within normal school-year calendars. Thirteen figures are included. Contains 51 references. (LMI)

This paper presents a proposal for a modified school choice program that may serve as a public policy compromise to the current politicized and entrenched choice or no-choice positions. The Three Year-Three Step Performance Guarantee involves both choice and vouchers. The use of vouchers, however, is not directed at reforming schools, but at helping parents in a democratic society fulfill their obligation to educate their children to their fullest potential. The paper challenges the view of educational vouchers as reform strategies and argues that choice and vouchers are more properly tools to help specific children for whom the public schools are not working. The proposal is a modified choice program that allows parents of low-achieving students to find schools in which their children can succeed. It is based on three steps: first, any child who attends a public school for at least three consecutive years should perform at specified standards in basic skills; second, parents of low-achieving students are given a choice: either enroll their child in another public school in their community or receive a needs-based scholarship voucher so their child can attend either a public school in another community or a private (nonreligious) school; and third, the new school will be given the same 3-year period to raise the child's performance to standard. If the school does not succeed, the voucher is terminated. It is argued that the proposal assists low-achieving students most in need of acquiring a good education; protects the rights of children; protects the rights of the state to ensure an educated citizenry; eliminates the threat of dismantling the public schools; and introduces accountability for performance. Contains 31 references. (LMI)

This paper considers the total-quality-management teachings of W. E. Deming as a basis for the redesign of educational-administration preparation programs. The performance domains developed by the National Commission for the Principalship (jointly sponsored by the National Association of Secondary School Principals and the National Association of Elementary School Principals) provide the framework for discussing Deming's theory. The commission criticized educational-administration programs as inadequate and called for the design of new programs. The paper describes the following domains that should be included in administrator-education programs: leadership, information collection and usage, staff development, and motivation. Deming's Fourteen Points, the concept of profound knowledge, the attributes of a leader, the Plan-Do-Study-Act cycle for improvement, and control charts are discussed. Two tables are included. The appendix contains a list of performance domains as defined by the commission. A list of the performance domains of the National Commission for the Principalship is appended. Contains 11 references. (Author/LMI)

Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge Tracing (LFKT) and Feature Aware Student knowledge Tracing (FAST) exhibit state of the art prediction accuracy. However, only few studies have analyzed the characteristics of these different models. In this paper, we therefore evaluate and compare properties of the models using synthetic data sets. We sample from a combined student model that encompasses all four models. Based on the true parameters of the data generating process, we assess model performance characteristics for over 66'000 parameter configurations and identify best and worst case performance. Using regression we analyze the influence of different sampling parameters on the performance of the models and study their robustness under different model assumption violations. [For complete proceedings, see ED560503.]

Besides measures of students' performances, a valid assessment of students' efficiency in a teaching process should also include measures of invested mental effort. The research presented herein covers several approaches in measuring students' mental effort including 5, 7 and 9-point Likert type scales, time on task, as well as eye tracking technique which in combination with performance measures provide valid information on students' success. Results of the research showed good correlation between mental effort assessed by 7 and 5-point Likert type scales and students' performance, while the use of the 9-point scale showed a low degree of correlation, thus recommending the use of a scales with 5 and 7 points for educational purposes over 9-point scales. The research presented herein illustrates how eye tracking can be used to support the evaluation of invested mental effort. Additionally, this method enabled the identification of some student difficulties in the analyzed area -- Stereochemistry. [For the full proceedings, see ED619611.]

Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs [Massive Open Online Courses], this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may not apply in blended courses with face to face and online components. We report on a study of integrated user-system interaction logs from 3 computer science courses using four online systems: LMS [Learning Management System], forum, version control, and homework system. Our results show that students rarely work across platforms in a single session, and that final class performance can be predicted from students' system use. [For the full proceedings, see ED593090.]

The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37 accepted as short papers. This year's conference features three invited talks: Tiffany Barnes, Professor at North Carolina State University in Raleigh, North Carolina; Jodi Forlizzi, Geschke Director of the HCI Institute and Professor at Carnegie Mellon University; and Jim Larimore, Chief Officer of Center for Equity in Learning at ACT, Inc. Together with the "Journal of Educational Data Mining" ("JEDM"), the EDM 2018 conference supports a "JEDM" Track that provides researchers a venue to deliver more substantial mature work than is possible in a conference proceeding and to present their work to a live audience. Three such papers are featured this year. The papers submitted to this track followed the "JEDM" peer review process. The main conference invited contributions to an Industry Track in addition to the main track. The EDM 2018 Industry Track received ten submissions of which six were accepted, a tangible improvement over last year, with only four submissions total, all of which were accepted. This expansion of the industry track represents an intentional goal to better connect industry researchers with the academic research community. The EDM conference continues its tradition of providing opportunities for young researchers to present their work and receive feedback from their peers and senior researchers. The doctoral consortium this year features 14 such presentations, more than double compared to the prior year. In addition to the main program, there are four workshops: (1) Educational Data Mining in Computer Science Education (CSEDM); (2) Proposal Policy & EDM: Norms, Risks, and Safeguards; (3) replicate.education: A Workshop on Large Scale Education Replication; and (4) Scientific Findings from the ASSISTments Longitudinal Data.

To optimize the benefits of game-based practice within Intelligent Tutoring Systems (ITSs), researchers examine how game features influence students' motivation and performance. The current study examined the influence of game features and individual differences (reading ability and learning intentions) on motivation and performance. Participants (n = 58) viewed lesson videos in iSTART-2, an ITS designed to improve reading comprehension skills, and practiced with either a game-like activity or a minimally game-like activity. No main effects of game environment were observed. However, there was an interaction between game environment and pretest learning intentions in predicting students' self-reported effort. The correlation between learning intentions and self-reported effort was not significant for students who practiced with the more game-like activity, whereas it was for students who practiced in the less game-like activity. We discuss the implications for this interaction and how it might drive future research. [This paper was published in: "Artificial Intelligence in Education, 17th International Conference, Proceedings," Springer, Cham, 2015, pp. 642-45.]

Poor motivation is commonly cited as a concern when interpreting results from low-stakes standardized tests administered to postsecondary students. This study investigates the associations between test administration procedures and students' self-reported effort and performance on the Collegiate Learning Assessment (CLA), an open-ended test of college students' critical-thinking and writing skills. Coefficient estimates from a series of hierarchical linear models revealed that paying students to take tests and offering performance-based incentives were positively associated with effort and performance. Mandatory testing, however, was negatively associated with effort and performance. Faculty involvement in recruiting, giving extra course credit, and offering prize raffle entries were not associated with effort or performance. Effort appeared to mediate the relationship between some test administration variables (e.g., payment and mandatory testing) and performance. [Paper presented at the Annual Meeting of the American Educational Research Association (Philadelphia, PA).]

This paper draws from research on individual and organizational learning to explore the opportunities for creating new models of schooling and to explain why many reform efforts end up producing incremental rather than radical changes. To do so, the study documents the evolution of two organizations that have worked to launch new, alternative schools in New York City. Despite differences in approach and philosophy, both appear to be expanding from a focus on l replicating new schools to "unbundling" their resources and services to support the work of both new and existing schools. Such an approach could lead to new developments, but it may also reinforce many of the conventional practices in schools that contribute to inequitable outcomes.

Taking the position that performance ethnography should be a viable and valued alternative and/or supplement to print ethnography, this paper explores ways to integrate phenomena that are visual, aural, and dynamic into existing scholarly practices. The paper advances one solution: create mechanisms for reproduction and distribution that have the advantages of printed text by using multimedia technology. The paper first discusses personal uses of performance in the practice of ethnography and elsewhere and then examines some of the critical discourse that has recently surfaced in the scholarly literature supporting the call for alternatives to print ethnography. The paper notes that one criticism of performance is that it holds great potential for self-indulgence, especially when personal narrative forms the core of the performance. It also points out that, when all is said and done, performance ethnography is also problematic for the academy largely because it simply and basically is not print. The paper then discusses the advantages of the print medium, given the kinds of work that have to get done in representing scholarly research. The paper also considers the ways in which performance, combined with multimedia technology, might be integrated into traditional practices of scholarship in an emergent, recombinant form and explores how unanticipated advantages of such an integration might accrue to those performance studies, cultural studies, and communication studies scholars involved in both research and instruction. (Contains numerous photographs of performance and 26 references.) (NKA)