The spacing effect in intentional and incidental free recall by children and adults: Limits on the automaticity hypothesis

Toppino, Thomas C.; Fearnow-Kenney, Melodie; Kiepert, Marissa H.; Teremula, Amanda C.

doi:10.3758/mc.37.3.316

Cited by 22 publications

(10 citation statements)

References 38 publications

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“…First, the distributed-practice effect is sometimes observed with incidental processing (e.g., R. L. Greene, 1989; Toppino, Fearnow-Kenney, Kiepert, & Teremula, 2009); it is not eliminated across the board, but the average effect size is slightly (albeit significantly) smaller. Second, the type of processing learners engage in may covary with the intentionality of their learning, with students being more likely to extract meaning from materials when they are deliberately trying to learn them.…”

Section: Reviewing the Learning Techniquesmentioning

confidence: 99%

Improving Students’ Learning With Effective Learning Techniques

Dunlosky

Rawson

Marsh

et al. 2013

Psychol Sci Public Interest

2,215

924

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Many students are being left behind by an educational system that some people believe is in crisis. Improving educational outcomes will require efforts on many fronts, but a central premise of this monograph is that one part of a solution involves helping students to better regulate their learning through the use of effective learning techniques. Fortunately, cognitive and educational psychologists have been developing and evaluating easy-to-use learning techniques that could help students achieve their learning goals. In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility. We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work. The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice. To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension. We attempted to provide thorough reviews for each technique, so this monograph is rather lengthy. However, we also wrote the monograph in a modular fashion, so it is easy to use. In particular, each review is divided into the following sections: General description of the technique and why it should work How general are the effects of this technique? 2a. Learning conditions 2b. Student characteristics 2c. Materials 2d. Criterion tasks Effects in representative educational contexts Issues for implementation Overall assessment The review for each technique can be read independently of the others, and particular variables of interest can be easily compared across techniques. To foreshadow our final recommendations, the techniques vary widely with respect to their generalizability and promise for improving student learning. Practice testing and distributed practice received high utility assessments because they benefit learners of different ages and abilities and have been shown to boost students' performance across many criterion tasks and even in educational contexts. Elaborative interrogation, self-explanation, and in...

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Section: Reviewing the Learning Techniquesmentioning

confidence: 99%

Improving Students’ Learning With Effective Learning Techniques

Dunlosky

Rawson

Marsh

et al. 2013

Psychol Sci Public Interest

2,215

924

View full text Add to dashboard Cite

show abstract

“…Would you like to play a game?" (see, e.g., Andrews & Halford, 2002;Carneiro, Fernandez, & Dias, 2009;Hanauer & Brooks, 2003;Price & Connolly, 2006;Raijmakers, Dolan, & Molenaar, 2001;Thibaut, French, & Vezneva, 2010;Toppino, Fearnow-Kenney, Kiepert, & Teremula, 2009;Yuzawa, 2001).…”

Section: Introductionmentioning

confidence: 99%

Gamelike features might not improve data

et al. 2012

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Many psychological experiments require participants to complete lots of trials in a monotonous task, which often induces boredom. An increasingly popular approach to alleviate such boredom is to incorporate gamelike features into standard experimental tasks. Games are assumed to be interesting and, hence, motivating, and better motivated participants might produce better data (with fewer lapses in attention and greater accuracy). Despite its apparent prevalence, the assumption that gamelike features improve data is almost completely untested. We test this assumption by presenting a choice task and a change detection task in both gamelike and standard forms. Response latency, accuracy, and overall task performance were unchanged by gamelike features in both experiments. We present a novel cognitive model for the choice task, based on particle filtering, to decorrelate the dependent variables and measure performance in a more psychologically meaningful manner. The model-based analyses are consistent with the hypothesis that gamelike features did not alter cognition. A postexperimental questionnaire indicated that the gamelike version provided a more positive and enjoyable experience for participants than the standard task, even though this subjective experience did not translate into data effects. Although our results hold only for the two experiments examined, the gamelike features we incorporated into both tasks were typical of-and at least as salient and interesting as those usually used by-experimental psychologists. Our results suggest that modifying an experiment to include gamelike features, while leaving the basic task unchanged, may not improve the quality of the data collected, but it may provide participants with a better experimental experience.

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“…One intervention postulated to be helpful is the spacing effect. This refers to educational encounters, which are spaced and repeated over time (spaced distribution), resulting in more efficient and improved retention of learning, compared with more concentrated educational encounters ( 44 , 45 ). Ojha et al designed a pediatric critical care scenario management program using spaced education model to look at the impact of repeated observation of routinely scheduled demonstrations of critical pediatric illness scenarios.…”

Section: Future Researchmentioning

confidence: 99%

Review of Simulation in Pediatrics: The Evolution of a Revolution

et al. 2015

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Recent changes in medical education have highlighted the importance of experiential learning. Simulation is one model that has gained significant attention in the last decade and has been widely adopted as a training and assessment tool in medical education. Pediatric simulation has been utilized to teach various skills including resuscitation and trauma management, procedural skills, and team training. It is also a valuable tool for health care educators, as it allows learners to achieve competence without putting patients at risk. Recent literature demonstrates increased retention of knowledge and skills after simulation-based training. Further research is required to improve current simulation curriculums, develop validated assessment tools, and to demonstrate improved clinical outcomes after simulation-based training. We conducted an online search of original and review articles related to simulation and pediatric medical education and provide an overview of the role and utility of simulation in pediatrics.Key PointsSimulation in pediatrics has been widely accepted and adapted as a training and assessment tool in medical education.Simulation in pediatrics has been utilized to teach various skills including resuscitation and trauma management, procedural skills, and team training.Further research is required to improve current simulation curriculums, to develop validated assessment tools, and to demonstrate improved clinical outcomes after simulation-based training.

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The spacing effect in intentional and incidental free recall by children and adults: Limits on the automaticity hypothesis

Cited by 22 publications

References 38 publications

Improving Students’ Learning With Effective Learning Techniques

Improving Students’ Learning With Effective Learning Techniques

Gamelike features might not improve data

Review of Simulation in Pediatrics: The Evolution of a Revolution

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