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Showing all 12 results Save | Export
Victoria Crisp; Sylvia Vitello; Abdullah Ali Khan; Heather Mahy; Sarah Hughes – Research Matters, 2025
This research set out to enhance our understanding of the exam techniques and types of written annotations or markings that learners may wish to use to support their thinking when taking digital multiple-choice exams. Additionally, we aimed to further explore issues around the factors that contribute to learners writing less rough work and…
Descriptors: Computer Assisted Testing, Test Format, Multiple Choice Tests, Notetaking
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Yang, Albert C. M.; Chen, Irene Y. L.; Flanagan, Brendan; Ogata, Hiroaki – Educational Technology & Society, 2021
Precision education is a new challenge in leveraging artificial intelligence, machine learning, and learning analytics to enhance teaching quality and learning performance. To facilitate precision education, text marking skills can be used to determine students' learning process. Text marking is an essential learning skill in reading. In this…
Descriptors: Grading, Computer Assisted Testing, Automation, Artificial Intelligence
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Frost, Kellie; Wigglesworth, Gillian; Clothier, Josh – Language Assessment Quarterly, 2021
The use of integrated tasks to test English-speaking skills raises questions about the impact of comprehension on test score outcomes, and the impact of stimulus materials on test-taker strategic behaviours. This study analysed speaking performances and verbal report data to examine the strategies used by test takers at different levels of…
Descriptors: Task Analysis, Second Language Learning, English (Second Language), Language Tests
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Zimbardi, Kirsten; Colthorpe, Kay; Dekker, Andrew; Engstrom, Craig; Bugarcic, Andrea; Worthy, Peter; Victor, Ruban; Chunduri, Prasad; Lluka, Lesley; Long, Phil – Assessment & Evaluation in Higher Education, 2017
Feedback is known to have a large influence on student learning gains, and the emergence of online tools has greatly enhanced the opportunity for delivering timely, expressive, digital feedback and for investigating its learning impacts. However, to date there have been no large quantitative investigations of the feedback provided by large teams…
Descriptors: Student Evaluation, Feedback (Response), Academic Achievement, Achievement Gains
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Crossley, Scott A.; Kim, YouJin – Language Assessment Quarterly, 2019
The current study examined the effects of text-based relational (i.e., cohesion), propositional-specific (i.e., lexical), and syntactic features in a source text on subsequent integration of the source text in spoken responses. It further investigated the effects of word integration on human ratings of speaking performance while taking into…
Descriptors: Individual Differences, Syntax, Oral Language, Speech Communication
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Rosen, Yigal; Tager, Maryam – Journal of Educational Computing Research, 2014
Major educational initiatives in the world place great emphasis on fostering rich computer-based environments of assessment that make student thinking and reasoning visible. Using thinking tools engages students in a variety of critical and complex thinking, such as evaluating, analyzing, and decision making. The aim of this study was to explore…
Descriptors: Critical Thinking, Concept Mapping, Computer Assisted Testing, Foreign Countries
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Barrett, Matthew E.; Swan, Alexander B.; Mamikonian, Ani; Ghajoyan, Inna; Kramarova, Olga; Youmans, Robert J. – International Journal of Instruction, 2014
This study examined the encoding specificity principle in relation to traditional and computer-based note taking and assessment formats in higher education. Students (N = 79) took lecture notes either by hand (n = 40) or by computer (n = 39) and then completed either a computer or a paper-based assessment. When note taking and assessment formats…
Descriptors: Notetaking, Congruence (Psychology), Higher Education, College Students
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Macedo-Rouet, Monica; Ney, Muriel; Charles, Sandrine; Lallich-Boidin, Genevieve – Computers & Education, 2009
The use of computers to deliver course-related materials is rapidly expanding in most universities. Yet the effects of computer vs. printed delivery modes on students' performance and motivation are not yet fully known. We compared the impacts of Web vs. paper to deliver practice quizzes that require information search in lecture notes. Hundred…
Descriptors: Undergraduate Students, Notetaking, Tests, Lecture Method
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Carrell, Patricia L.; Dunkel, Patricia A.; Mollaun, Pamela – Applied Language Learning, 2004
With the goal of improving the reliability and validity of tests of English as a foreign language, in particular with respect to the question of whether to allow notetaking on EFL/ESL computer-based listening comprehension tests, the present study examined the effects on ESL listening comprehension of notetaking (allowed or disallowed) in relation…
Descriptors: English (Second Language), Listening Comprehension Tests, Computer Assisted Testing, Notetaking
Benton, Stephen L.; And Others – 1994
Two experiments were conducted to investigate why lecture notes aid expository writing after a 1-week delay between lecture acquisition and essay writing. Experiment 1 examines the context hypothesis that deactivation of lecture schema must occur before attempts to reinstantiate context can aid writing. Results with 74 undergraduate students did…
Descriptors: Cognitive Processes, Computer Assisted Testing, Creativity, Essays
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Carrell, Patricia L. – ETS Research Report Series, 2007
Utilizing a pre- and posttest research design, with an instructional intervention of good practices in notetaking, the notes taken by examinees during a computer-based listening comprehension test prior to and following the instructional intervention were examined for particular notetaking strategies. Questionnaires probed perceptions of the…
Descriptors: Notetaking, Pretests Posttests, Correlation, English (Second Language)
Henderson, George; Nash, Susan Smith – Charles C. Thomas, Publisher, Ltd, 2007
This book will improve the quality of instruction that college students need. It makes numerous suggestions that must be tended to when teachers instruct students. For example, the authors speculate about ways teachers can present what may at times seem to be a mountain of information without burying students under it; why teachers must…
Descriptors: Notetaking, Short Term Memory, Internet, Discussion Groups