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Barret, Mandy; Branson, Lisa; Carter, Sheryl; DeLeon, Frank; Ellis, Justin; Gundlach, Cirrus; Lee, Dale – Inquiry, 2019
Artificial intelligence (AI) technology is becoming the basis for business. Most businesses use it to improve the customer experience. The education community is just beginning to find ways to successfully implement AI for staff and students. Artificial Intelligence should be leveraged to create a better student experience. For example, Elon…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Educational Opportunities
Kwong, Theresa; Hafiz, Muhammad; Lau, Peter; Chan, Isaac – Journal on Excellence in College Teaching, 2018
Differences in cultural background and prior academic background significantly affect the perception of academic integrity and ethics (AIE) among university students. While upholding the highest standards of AIE is crucial both academically and professionally, such abstract concepts are difficult to teach in the traditional classroom. With mobile…
Descriptors: Integrity, Ethics, Cultural Background, Prior Learning
Pratt, Justin M.; Yezierski, Ellen J. – Chemistry Education Research and Practice, 2018
Conducting qualitative research in any discipline warrants two actions: accessing participants and eliciting their ideas. In chemistry education research (CER), survey techniques have been used to increase access to participants and diversify samples. Interview tasks (such as card sorting, using demonstrations, and using simulations) have been…
Descriptors: Chemistry, Science Education, Qualitative Research, Scientific Research
Zeng, Ziheng; Chaturvedi, Snigdha; Bhat, Suma – International Educational Data Mining Society, 2017
Characterizing the nature of students' affective and emotional states and detecting them is of fundamental importance in online course platforms. In this paper, we study this problem by using discussion forum posts derived from large open online courses. We find that posts identified as encoding confusion are actually manifestations of different…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
Miller, Cynthia; Cohen, Benjamin; Yang, Edith; Pellegrino, Lauren – MDRC, 2020
College students have a better chance of succeeding in school when they receive high-quality advising. High-quality advising, when characterized by frequent communications between advisers and students, early outreach to students showing signs of academic or nonacademic struggles, and personalized guidance that addresses individual student needs,…
Descriptors: College Students, Academic Advising, Technology Uses in Education, Faculty Advisers
Roberts, Lynne D.; Howell, Joel A.; Seaman, Kristen – Technology, Knowledge and Learning, 2017
With the increased capability of learning analytics in higher education, more institutions are developing or implementing student dashboards. Despite the emergence of dashboards as an easy way to present data to students, students have had limited involvement in the dashboard development process. As part of a larger program of research examining…
Descriptors: Higher Education, Data Collection, Data Analysis, Educational Research
Aranha, Solange; Leone, Paola – Research-publishing.net, 2016
This contribution aims at (1) discussing the characteristics of collecting, filing and storing data to have a databank of oral interactions between university students whose main objective is the learning of a second language through teletandem; and (2) defining the steps for further collections and storage. Our data are Skype sessions of foreign…
Descriptors: Databases, Data Collection, College Students, Speech Communication
Ye, Li; Oueini, Razanne; Dickerson, Austin P.; Lewis, Scott E. – Chemistry Education Research and Practice, 2015
This study used a series of text message inquiries sent to General Chemistry students asking: "Have you studied for General Chemistry I in the past 48 hours? If so, how did you study?" This method for collecting data is novel to chemistry education research so the first research goals were to investigate the feasibility of the technique…
Descriptors: Computer Mediated Communication, Telecommunications, Science Instruction, Chemistry
Wise, Alyssa Friend; Zhao, Yuting; Hausknecht, Simone Nicole – Journal of Learning Analytics, 2014
This paper describes an application of learning analytics that builds on an existing research program investigating how students contribute and attend to the messages of others in asynchronous online discussions. We first overview the E-Listening research program and then explain how this work was translated into analytics that students and…
Descriptors: Data Collection, Data Analysis, Asynchronous Communication, Computer Mediated Communication
Kennedy, Gregor; Ioannou, Ioanna; Zhou, Yun; Bailey, James; O'Leary, Stephen – Australasian Journal of Educational Technology, 2013
The analysis and use of data generated by students' interactions with learning systems or programs--learning analytics--has recently gained widespread attention in the educational technology community. Part of the reason for this interest is based on the potential of learning analytic techniques such as data mining to find hidden patterns in…
Descriptors: Data Analysis, Interaction, Educational Technology, Data Collection
Bacino Thiessen, Michelle – ProQuest LLC, 2015
This qualitative study explored the experiences of an online learner at a community college. The purpose of the study was to investigate community college students' perception of online courses through an examination of their experiences with online learning. The community of inquiry theory was used as a guide to better understand the importance…
Descriptors: Student Satisfaction, Electronic Learning, Community Colleges, College Students
Chiu, Ming Ming; Fujita, Nobuko – Journal of Learning Analytics, 2014
Online forums (synchronous and asynchronous) offer exciting data opportunities to analyze how people influence one another through their interactions. However, researchers must address several analytic difficulties involving the data (missing values, nested structure [messages within topics], non-sequential messages), outcome variables (discrete…
Descriptors: Computer Mediated Communication, Data Collection, Data Analysis, Discourse Analysis
Xu Ryan, Qing – ProQuest LLC, 2013
The ability to solve problems in a variety of contexts is becoming increasingly important in our rapidly changing technological society. Problem-solving is a complex process that is important for everyday life and crucial for learning physics. Although there is a great deal of effort to improve student problem solving skills throughout the…
Descriptors: Coaching (Performance), Electronic Learning, Computer Mediated Communication, Computer Assisted Instruction
Collentine, Karina – Language Learning & Technology, 2011
This study contributes to the research on learner autonomy by examining the relationship between Little's (1991) notions of "independent action" and "decision-making", input, and L2 production in computer-assisted language learning (CALL). Operationalizing "independent action" and "decision-making" with Dam's (1995) definition that focuses on…
Descriptors: Second Language Learning, Computer Assisted Instruction, Educational Technology, Decision Making
Penner, Nikolai; Schulze, Mathias – Journal of Interactive Learning Research, 2010
This paper addresses several components of successful language-learning methodologies--group work, task-based instruction, and wireless computer technologies--and examines how the interplay of these three was perceived by students in a second-year university foreign-language course. The technology component of our learning design plays a central…
Descriptors: Student Attitudes, Teaching Methods, Group Activities, Grouping (Instructional Purposes)
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