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van der Schaaf, Marieke; Donkers, Jeroen; Slof, Bert; Moonen-van Loon, Joyce; van Tartwijk, Jan; Driessen, Eric; Badii, Atta; Serban, Ovidiu; Ten Cate, Olle – Educational Technology Research and Development, 2017
Electronic portfolios (E-portfolios) are crucial means for workplace-based assessment and feedback. Although E-portfolios provide a useful approach to view each learner's progress, so far options for personalized feedback and potential data about a learner's performances at the workplace often remain unexploited. This paper advocates that…
Descriptors: Personnel Evaluation, Evaluation Methods, Feedback (Response), Electronic Publishing
Shaw, Alissa Campbell – ProQuest LLC, 2017
Two binary logistic regression analyses were conducted across survey data from 254 master's-level graduates to answer research questions about predicting Willingness to Give to their graduate alma mater and predicting Actual Alumni Giving behavior to their graduate alma mater. The predictor variables are dimensions from the community of inquiry…
Descriptors: Alumni, Graduate Students, Private Financial Support, Educational Finance
Chan, Hsun-Yu – Texas Education Research Center, 2017
College education becomes increasingly important for individuals' career prospect. However, many students enter college academically unprepared (Jackson & Kurlaender, 2014). As a response, high school curriculum is tasked as the gatekeeper of students' academic proficiency that equips students with essential knowledge and skills for…
Descriptors: High School Students, Academic Achievement, Socioeconomic Background, Racial Differences
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Wulff, Dirk U.; Pachur, Thorsten – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
What are the cognitive mechanisms underlying subjective valuations formed on the basis of sequential experiences of an option's possible outcomes? Ashby and Rakow (2014) have proposed a sliding window model (SWIM), according to which people's valuations represent the average of a limited sample of recent experiences (the size of which is estimated…
Descriptors: Experimental Psychology, Cognitive Psychology, Modeling (Psychology), Models
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DiCerbo, Kristen – Learning, Media and Technology, 2016
The volume of data that can be captured and stored from students' everyday interactions with digital environments allows for the creation of models of student knowledge, skills, and attributes unobtrusively. However, models and techniques for transforming these data into information that is useful for educators have not been established. This…
Descriptors: Bayesian Statistics, Educational Technology, Electronic Learning, Learning Processes
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Lim, Vivian; Rubel, Laurie; Shookhoff, Lauren; Sullivan, Mathew; Williams, Sarah – Mathematics Teaching in the Middle School, 2016
The lottery has rich potential for mathematical explorations. It serves as a real-world context to explore concepts of permutations, combinations, sample space, and probability in terms of making sense of the lottery games. The lottery offers additional possibilities in terms of scaling, data analysis, and spatial analysis. Finally, by readily…
Descriptors: Mathematics, Mathematics Education, Games, Probability
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Butcher, Greg Q.; Rodriguez, Juan; Chirhart, Scott; Messina, Troy C. – Bioscene: Journal of College Biology Teaching, 2016
In order to increase students' awareness for and comfort with mathematical modeling of biological processes, and increase their understanding of diffusion, the following lab was developed for use in 100-level, majors/non-majors biology and neuroscience courses. The activity begins with generation of a data set that uses coin-flips to replicate…
Descriptors: Biology, Comparative Analysis, Simulation, Questionnaires
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Faraut, Mailys C. M.; Procyk, Emmanuel; Wilson, Charles R. E. – Learning & Memory, 2016
Unexpected outcomes can reflect noise in the environment or a change in the current rules. We should ignore noise but shift strategy after rule changes. How we learn to do this is unclear, but one possibility is that it relies on learning to learn in uncertain environments. We propose that acquisition of latent task structure during learning to…
Descriptors: Learning, Cognitive Processes, Animals, Error Patterns
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Kern, Holger L.; Stuart, Elizabeth A.; Hill, Jennifer; Green, Donald P. – Journal of Research on Educational Effectiveness, 2016
Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research,…
Descriptors: Educational Research, Generalization, Sampling, Participant Characteristics
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Sinclair, Michael; Dauerty, Helene; Alber, Mark – Science Teacher, 2016
Biomodeling is the study of the structures and behaviors of interacting biological entities such as molecules, cells, or organisms. While physical and chemical processes give rise to various spatial and temporal structures, even the simplest biological phenomenon is infinitely more complex (Kling 2004). Over the past decade, much of biomodeling…
Descriptors: Biology, Mathematical Models, Cytology, Probability
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Akhmetzyanova, Anna I. – International Journal of Environmental and Science Education, 2016
The relevance of this problem is related to the urgent need to explain peculiarities of anticipation and probabilistic forecasting in adolescence. It has revealed a contradiction: on the one hand, the problem of anticipation in ontogenesis is well developed, and, on the other hand, there remain understudied mechanisms of anticipation in…
Descriptors: Probability, Prediction, Adolescents, Foreign Countries
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Longford, Nicholas Tibor – Journal of Educational and Behavioral Statistics, 2016
We address the problem of selecting the best of a set of units based on a criterion variable, when its value is recorded for every unit subject to estimation, measurement, or another source of error. The solution is constructed in a decision-theoretical framework, incorporating the consequences (ramifications) of the various kinds of error that…
Descriptors: Decision Making, Classification, Guidelines, Undergraduate Students
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Klopfenstein, Kristin; Lively, Kit – Education Finance and Policy, 2016
When calculating class rank, high schools often give additional weight to grades earned in College Board Advanced Placement (AP) courses as an incentive for students to take hard courses. This paper examines changes in student course-taking behavior after an increase in AP grade weights at Texas high schools. We find that raising the magnitude of…
Descriptors: High School Students, Class Rank, Advanced Placement, Grades (Scholastic)
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Sponarski, Carly C.; Vaske, Jerry J.; Bath, Alistair J.; Loeffler, TA – Journal of Environmental Education, 2016
An experiential education program was designed to target risk perceptions and preventative measures that make people feel comfortable in human-coyote interactions. The research was conducted in a Canadian national park where a coyote caused a human fatality in 2009. Based on previous research, we explored the effects of an experience-based coyote…
Descriptors: Experiential Learning, Foreign Countries, Wildlife, Attitude Change
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Liu, Yating; Enderson, Mary C. – Mathematics Teacher, 2016
A mysterious conflict of solutions emerged when a group of tenth- and eleventh-grade students were studying a seemingly ordinary problem on combination and probability. By investigating the mysterious "conflicts" caused by multiple randomization procedures, students will gain a deeper understanding of what it means to perform a task…
Descriptors: High School Students, Grade 10, Grade 11, Probability
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