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Meng Qu – Education and Information Technologies, 2024
This paper introduces a Patron Counting and Analysis (PCA) system that leverages Wi-Fi-connection data to monitor space utilization and analyze visitor patterns in academic libraries. The PCA system offers real-time crowding information to the public and a comprehensive visitor analysis dashboard for library administrators. The system's…
Descriptors: Academic Libraries, Users (Information), Use Studies, Space Utilization
Mouri, Kousuke; Suzuki, Fumiya; Shimada, Atsushi; Uosaki, Noriko; Yin, Chengjiu; Kaneko, Keiichi; Ogata, Hiroaki – Interactive Learning Environments, 2021
This paper describes a method to collect data of which section of pages learners were browsing in digital textbooks without eye-tracking technologies. In previous researches on digital textbook systems, it was difficult to collect such data without using eye-tackers. However, eye-trackers cost a massive budget. Our proposed system automatically…
Descriptors: Data Analysis, Textbooks, Electronic Publishing, Data Collection
Woolverton, Genevieve Alice; Pollastri, Alisha R. – Educational Measurement: Issues and Practice, 2021
Within classrooms, psychologists and teachers use direct behavior observation methods, systematic behavior observations (SBOs) and direct behavior ratings (DBRs), to gather information about students' behaviors for the purposes of making decisions related to diagnosis and classroom management or behavioral feedback respectively. Observers use SBOs…
Descriptors: Student Behavior, Classroom Observation Techniques, Behavior Rating Scales, Behavior Patterns
Zhang, Mo; Guo, Hongwen; Liu, Xiang – International Educational Data Mining Society, 2021
We present an empirical study on the use of keystroke analytics to capture and understand how writers manage their time and make inferences on how they allocate their cognitive resources during essay writing. The results suggest three distinct longitudinal patterns of writing process that describe how writers approach an essay task in a writing…
Descriptors: Keyboarding (Data Entry), Learning Analytics, Data Collection, Cognitive Processes
Schermer, Maike; Fosker, Tim – International Journal of Research & Method in Education, 2020
Arguably one of the most valuable tools for investigating pupil behaviour in an educational environment is systematic classroom observation. Classroom observation is often cited as having the potential to enable research of the learning process in action. Low inference classroom observation instruments are designed to record a sequence of data…
Descriptors: Classroom Observation Techniques, Learning Processes, Intervals, Individual Differences
Kianersi, Sina; Luetke, Maya; Jules, Reginal; Rosenberg, Molly – International Journal of Social Research Methodology, 2020
Bias may be introduced in survey data collection when participants answer questions differently depending on interviewer gender. This could affect the validity of collected data, especially sensitive data. Using sexual behavior data collected in a 2017-2018 cross-sectional survey of Haitian women (n = 304), we evaluated the associations between…
Descriptors: Females, Foreign Countries, Responses, Surveys
Hu, Xiangen; Cai, Zhiqiang; Hampton, Andrew J.; Cockroft, Jody L.; Graesser, Arthur C.; Copland, Cameron; Folsom-Kovarik, Jeremiah T. – Grantee Submission, 2019
In this paper, we consider a minimalistic and behavioristic view of AIS to enable a standardizable mapping of both the behavior of the system and of the learner. In this model, the "learners" interact with the learning "resources" in a given learning "environment" following preset steps of learning…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Metadata, Behavior Patterns
Bezerra, Luis Naito Mendes; Silva, Márcia Terra – International Journal of Distance Education Technologies, 2020
In the current context of distance learning, learning management systems (LMSs) make it possible to store large volumes of data on web browsing and completed assignments. To understand student behavior patterns in this type of environment, educators and managers must rethink conventional approaches to the analysis of these data and use appropriate…
Descriptors: Learning Analytics, Data Collection, Class Size, Online Courses
Xu, Cuiqin; Xia, Jun – Computer Assisted Language Learning, 2021
The last two decades have witnessed a quick shift from pen-and-paper writing to computer keyboard writing. Corresponding to this shift in the writing medium are vigorous research efforts to understand new features of writing in computer keyboard settings. Using Inputlog7.0, this study investigated the writing process of 60 Chinese English as a…
Descriptors: Scaffolding (Teaching Technique), Writing Processes, Writing Skills, English (Second Language)
Borgmeier, Chris; Loman, Sheldon L.; Strickland-Cohen, M. Kathleen – Beyond Behavior, 2017
Students with persistent challenging behavior are present in nearly every classroom. Teachers need the knowledge and skills to understand student behavior and intervene effectively. This article presents a framework to guide teachers in understanding student behavior and feasible tools for collecting data about the function of student behavior.…
Descriptors: Student Behavior, Behavior Problems, Functional Behavioral Assessment, Data Collection
Godwin-Jones, Robert – Language Learning & Technology, 2021
Data collection and analysis is nothing new in computer-assisted language learning, but with the phenomenon of massive sets of human language collected into corpora, and especially integrated into systems driven by artificial intelligence, new opportunities have arisen for language teaching and learning. We are now seeing powerful artificial…
Descriptors: Data Collection, Academic Achievement, Learning Analytics, Computer Assisted Instruction
Martin, Andrew J.; Mansour, Marianne; Malmberg, Lars-Erik – Educational Psychology, 2020
Using mobile technology and experience sampling in junior high school, real-time motivation and engagement were explored at four-levels: between lessons (up to 2 lessons per day; Level 1), between days (5 days per week; L2), between weeks (4 weeks; L3), and between students (113 students; L4). Findings for a 'random effects' model revealed…
Descriptors: Student Motivation, Learner Engagement, Computer Use, Behavior Patterns
Zhu, Mengxiao; Zhang, Mo; Deane, Paul – ETS Research Report Series, 2019
The research on using event logs and item response time to study test-taking processes is rapidly growing in the field of educational measurement. In this study, we analyzed the keystroke logs collected from 761 middle school students in the United States as they completed a persuasive writing task. Seven variables were extracted from the…
Descriptors: Keyboarding (Data Entry), Data Collection, Data Analysis, Writing Processes
Du, Xin; Duivesteijn, Wouter; Klabbers, Martijn; Pechenizkiy, Mykola – International Educational Data Mining Society, 2018
Behavioral records collected through course assessments, peer assignments, and programming assignments in Massive Open Online Courses (MOOCs) provide multiple views about a student's study style. Study behavior is correlated with whether or not the student can get a certificate or drop out from a course. It is of predominant importance to identify…
Descriptors: Student Behavior, Assignments, Large Group Instruction, Online Courses
Lowe, Heather – Educational Technology, 2016
Dartmouth and MIT have developed educational behavior apps and wearable devices that collect contiguous streams of data from student users. Given the consent of the user, the app collects information about a student's physical activity, sleep patterns, and location to form conjectures about social and academic behavior. These apps have the…
Descriptors: Student Behavior, Data Collection, Courseware, Behavior Patterns