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Grineski, Sara; Daniels, Heather; Collins, Timothy; Morales, Danielle X.; Frederick, Angela; Garcia, Marilyn – Science Education, 2018
Research on the science, technology, engineering, and math (STEM) student development pipeline has largely ignored social class and instead examined inequalities based on gender and race. We investigate the role of social class in undergraduate student research publications. Data come from a sample of 213 undergraduate research participants…
Descriptors: Social Class, Writing for Publication, STEM Education, Undergraduate Students
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Erford, Bradley T.; Jackson, Jessica; Bardhoshi, Gerta; Duncan, Kelly; Atalay, Zumra – Measurement and Evaluation in Counseling and Development, 2018
Psychometric meta-analyses and reviews were provided for four commonly used suicidal ideation instruments: the Beck Scale for Suicide Ideation, the Suicide Ideation Questionnaire, the Suicide Probability Scale, and Columbia--Suicide Severity Rating Scale. Practical and technical issues and best use recommendations for screening and outcome…
Descriptors: Suicide, Psychological Patterns, Meta Analysis, Evaluation Methods
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Chen, Jie; Perie, Marianne – Computers in the Schools, 2018
Due to increased use of computer-based assessments, comparability studies are moving beyond paper-and-pencil versus computer-based assessments to analyze variances with computers. It is therefore practically important to determine whether screen size and definition of the device affect students' performance. Using data from a large school district…
Descriptors: Computer Assisted Testing, Laptop Computers, Computer System Design, Probability
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Whitehill, Jacob; Movellan, Javier – IEEE Transactions on Learning Technologies, 2018
We propose a method of generating teaching policies for use in intelligent tutoring systems (ITS) for concept learning tasks [1], e.g., teaching students the meanings of words by showing images that exemplify their meanings à la Rosetta Stone [2] and Duo Lingo [3]. The approach is grounded in control theory and capitalizes on recent work by [4],…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Educational Policy, Comparative Analysis
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Man, Kaiwen; Harring, Jeffery R.; Ouyang, Yunbo; Thomas, Sarah L. – International Journal of Testing, 2018
Many important high-stakes decisions--college admission, academic performance evaluation, and even job promotion--depend on accurate and reliable scores from valid large-scale assessments. However, examinees sometimes cheat by copying answers from other test-takers or practicing with test items ahead of time, which can undermine the effectiveness…
Descriptors: Reaction Time, High Stakes Tests, Test Wiseness, Cheating
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Bross, Leslie Ann; Common, Eric Alan; Oakes, Wendy Peia; Lane, Kathleen Lynne; Menzies, Holly M.; Ennis, Robin Parks – Beyond Behavior, 2018
High-probability request sequence (HPRS) is a low-intensity strategy designed to increase student compliance by creating behavioral momentum. Momentum is established by providing three to five requests that a noncompliant student is most likely to do followed quickly by a less preferred request. Herein, we describe a step-by-step process for using…
Descriptors: Probability, Classroom Techniques, Teaching Methods, Compliance (Psychology)
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Talanquer, Vicente – International Journal of Science Education, 2018
One of the central goals of modern science and chemistry education is to develop students' abilities to understand complex phenomena, and productively engage in explanation, justification, and argumentation. To accomplish this goal, we should better characterise the types of reasoning that we expect students to master in the different scientific…
Descriptors: Science Education, Chemistry, Science Process Skills, Abstract Reasoning
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Starns, Jeffrey J.; Ma, Qiuli – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
The two-high-threshold (2HT) model of recognition memory assumes that people make memory errors because they fail to retrieve information from memory and make a guess, whereas the continuous unequal-variance (UV) model and the low-threshold (LT) model assume that people make memory errors because they retrieve misleading information from memory.…
Descriptors: Guessing (Tests), Recognition (Psychology), Memory, Tests
Lesisko, Lee J.; Mauro, Robert D.; Sebelin, Jane S. – Online Submission, 2018
This study provides K-12 students, as well as parents/guardians, with an understanding of the concept of plagiarism in an online academic environment. The authors begin with real world scenarios that allow the reader to understand the setting and context of the problem. The impact of plagiarism is explored through a cost benefit analysis from each…
Descriptors: Elementary Secondary Education, Plagiarism, Online Courses, Probability
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Stevenson, Dean L.; Beckmann, Sybilla; Johnson, Sheri E.; Kang, Rui – North American Chapter of the International Group for the Psychology of Mathematics Education, 2018
We have extended two perspectives of proportional reasoning to solve problems based in probability. Four future middle grade teachers were enrolled in a mathematics content course that emphasized reasoning about multiplication with quantities. The course expected future teachers to generate and explain methods for solving proportions. Probability…
Descriptors: Problem Solving, Probability, Middle School Teachers, Preservice Teachers
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Kang, Lili; Peng, Fei; Zhu, Yu – Studies in Higher Education, 2021
Using the China Family Panel Studies, we identify the subjects studied by vocational college and university graduates, with the latter group further divided into ordinary and key universities. While the returns are around 8-10% to attending colleges and ordinary universities, there are higher returns of 12-16% per annum to attending the more…
Descriptors: Higher Education, Institutional Characteristics, Foreign Countries, College Graduates
Jameson, Ellen; Whitney-Smith, Rachael; Macey, Darren; Morony, Will; Benson-Lidholm, Anne-Marie; Leigh-Lancaster, David – Mathematics Education Research Group of Australasia, 2021
This paper reports on a new initiative of collaborative work between the Australian Curriculum, Assessment and Reporting Authority (ACARA) and Cambridge University as part of the 2020-21 review of the Australian Curriculum: Mathematics Foundation -- Year 10. The ACARA mathematics curriculum development team worked with the Cambridge Mathematics…
Descriptors: Mathematics Instruction, National Curriculum, Secondary School Students, Grade 10
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Liu, Zhi; Yang, Chongyang; Rüdian, Sylvio; Liu, Sannyuya; Zhao, Liang; Wang, Tai – Interactive Learning Environments, 2019
Textual data, as a key carrier of learning feedback, is continuously produced by many students within course forums. The temporal nature of discussion requires students' emotions and concerned aspects (e.g. teaching styles, learning activities, etc.) to be dynamically tracked for understanding learning requirements. To characterize dynamics of…
Descriptors: Online Courses, Student Attitudes, Emotional Response, Models
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Mezhennaya, Natalia M.; Pugachev, Oleg V. – European Journal of Contemporary Education, 2019
Typical difficulties in learning probabilistic subjects are concerned with big data, complicated formulas and inconvenient figures in statistical analyses. The present research considers the usage of innovative teaching methods (e.g. electronic summary of lectures, presentations of lecture courses, task solution templates, electronic training…
Descriptors: Mathematics Instruction, Probability, Statistics, Teaching Methods
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Calvert, Carol; Hilliam, Rachel – Open Learning, 2019
Across the Higher Education (HE) sector student feedback is used to feed into university processes and guide decision making. In this study, data gathered allowed the authors to investigate a hitherto neglected, but important, cohort of successful students -- those who succeeded when all the odds were stacked against them. The identified group of…
Descriptors: Student Attitudes, Feedback (Response), School Holding Power, Undergraduate Students
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