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Exploring the Use of Self-explanation Prompts in a Collaborative Learning EnvironmentJanuary 2018 (has links)
abstract: A recorded tutorial dialogue can produce positive learning gains, when observed and used to promote discussion between a pair of learners; however, this same effect does not typically occur when an leaner observes a tutorial dialogue by himself or herself. One potential approach to enhancing learning in the latter situation is by incorporating self-explanation prompts, a proven technique for encouraging students to engage in active learning and attend to the material in a meaningful way. This study examined whether learning from observing recorded tutorial dialogues could be made more effective by adding self-explanation prompts in computer-based learning environment. The research questions in this two-experiment study were (a) Do self-explanation prompts help support student learning while watching a recorded dialogue? and (b) Does collaboratively observing (in dyads) a tutorial dialogue with self-explanation prompts help support student learning while watching a recorded dialogue? In Experiment 1, 66 participants were randomly assigned as individuals to a physics lesson (a) with self-explanation prompts (Condition 1) or (b) without self-explanation prompts (Condition 2). In Experiment 2, 20 participants were randomly assigned in 10 pairs to the same physics lesson (a) with self-explanation prompts (Condition 1) or (b) without self-explanation prompts (Condition 2). Pretests and posttests were administered, as well as other surveys that measured motivation and system usability. Although supplemental analyses showed some significant differences among individual scale items or factors, neither primary results for Experiment 1 or Experiment 2 were significant for changes in posttest scores from pretest scores for learning, motivation, or system usability assessments. / Dissertation/Thesis / Doctoral Dissertation Educational Technology 2018
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Using subgoal learning and self-explanation to improve programming educationMargulieux, Lauren Elizabeth 27 May 2016 (has links)
The present study combined subgoal learning and self-explanation frameworks to improve problem solving performance. Subgoal learning has been used to promote retention and transfer in procedural domains, such as programming. The primary method for learning subgoals, however, has been through passive learning methods, and passive learning methods are typically less effective than constructive learning methods. To promote constructive methods of learning subgoals, a subgoal learning framework was used to guide self-explanation. Self-explanation is an effective method for engaging learners to make sense of new information based on prior knowledge and logical reasoning. Self-explanation is typically more effective when learners receive some guidance, especially if they are novices, because it helps them to focus their attention on relevant information. In the present study, only some of the constructive learning methods produced better problem solving performance than passive learning methods. Learners performed best when they learned constructively and either received hints about the subgoals of the procedure or received feedback on the self-explanations that they constructed, but not when they received both hints and feedback. When students received both types of guidance, they did not perform better than those who learned subgoals through passive learning methods. These findings suggest that constructive learning of subgoals can further improve the benefits of learning subgoals, but there is an optimal level of guidance for students engaging in constructive learning. Providing too much guidance can be as detrimental as providing too little. This nuance is important for educators who engage their students in constructive learning and self-explanation to recognize and promote the best results.
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Self-explanation and planning: a microgenetic study of preschoolers' strategy use on the Tower of Hanoi.Miller, Michael Robert 29 August 2011 (has links)
In early childhood, planning provides a basis for organizational skills that are useful for future school performance (Perez & Gauvain, 2009). However, research shows that preschoolers’ planning abilities are limited because they often fail to consider task demands, are inefficient at self-monitoring, and are unlikely to use strategies to their advantage (Gardner & Rogoff, 1990). The present study examined whether preschoolers could improve their planning skills by consciously drawing connections between objects and events through the use of verbal self-explanations. A microgenetic design was used in order to repeatedly measure preschoolers’ performance on the Tower of Hanoi (ToH) task over a period of 6 to 8 weeks. Forty-five children between the ages of 4 and 6 years were randomly assigned to 1 of 3 conditions: self-explanation, no self-explanation, and control. Each child was administered a pretest, 3 micro sessions based on condition, and a posttest. In addition to ToH performance, children also were measured on inhibitory control, working memory, short-term memory, and verbal ability at pretest, and on a novel planning task, the Box-ToH, at posttest. Multilevel models were used to analyze the data at the between- and within-person levels. Although no differences were found in ToH performance over time between conditions, preschoolers’ use of self-explanations and strategies were independently related to individual improvements in ToH performance over time. Moreover, preschoolers’ improvements in ToH performance were not reducible to age-related increases, inhibitory control demands, working memory, short-term memory, or verbal ability. Lastly, findings did not support preschoolers’ ability to transfer their knowledge of strategies on the ToH to the Box-ToH. Overall, the present study demonstrated that self-explanations and strategy use are both important predictors of understanding individual changes in planning performance during the preschool years. These findings have important implications in terms of improving preschoolers’ executive function skills and preparing children for early academic success. / Graduate
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Enhancing Students’ Ability to Correct Misconceptions in Natural Selection with Refutational Texts and Self-ExplanationJanuary 2020 (has links)
abstract: This study examined the effects of different constructed response prompts and text types on students’ revision of misconceptions, comprehension, and causal reasoning. The participants were randomly assigned to prompt (self-explain, think-aloud) and text type (refutational, non-refutational) in a 2x2, between-subjects design. While reading, the students were prompted to write responses at regular intervals in the text. After reading, students were administered the conceptual inventory of natural selection (CINS), for which a higher score indicates fewer misconceptions of natural selection. Finally, students were given text comprehension questions, and reading skill and prior knowledge measures. Linear mixed effects (LME) models showed that students with better reading skill and more prior knowledge had a higher CINS score and better comprehension compared to less skilled students, but there were no effects of text type or prompt. Linguistic analysis of students’ responses demonstrated a relationship of prompt, text, and reading skill on students’ causal reasoning. Less skilled students exhibited greater causal reasoning when self-explaining a non-refutational text compared to less skilled students prompted to think-aloud, and less skilled students who read the refutational text. The results of this study demonstrate a relationship between reading skill and misconceptions in natural selections. Furthermore, the linguistic analyses suggest that less skilled students’ causal reasoning improves when prompted to self-explain. / Dissertation/Thesis / Masters Thesis Psychology 2020
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The Developmental and Teacher-Related Mediating Effects of Mathematics Vocabulary Use on Algebra LearningMcGinn, Kelly Marie January 2015 (has links)
Today, it is almost expected that students learn to precisely communicate their mathematical thinking. In fact, the CCSS stress the importance of precision when communicating with others (CCSSI, 2010). Due to this drive towards precise discourse, it is easy to lose sight of the original purpose for mathematical communication- to help students develop a better understanding of the mathematical concepts (NCTM, 2000). Self-explanation prompts are a common tool used to foster mathematical communication (Chi, 2000). Due to the increased popularity given to the use of self-explanation prompts, many have explored the mediating variables that may influence the effectiveness of this tool on student learning. Unfortunately, the effect of the precision of mathematics vocabulary used when responding has not yet been explored. Findings from this study support the use of both formal and informal expressions to explain a mathematical concept. The key is that students attempt to explain the concept- it does not seem to matter whether they do it formally or informally. The use of informal expressions may however allow the teacher to make a better judgment as to whether the student has a misunderstanding, since the correctness of informal expressions predict procedural knowledge, while the correctness of formal expressions do not. In addition, consistent attempts to use both formal and informal expressions is associated with higher self-explanation scores, and conceptual and procedural knowledge, suggesting that teachers should promote a consistent attempt to explains concepts, regardless of the type of language used. Finally, there is some evidence that the teachers' stress of the importance of precise terminology use influences students' actual use of this formal language. / Educational Psychology
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Evaluating the benefits of worked examples in a constraint-based tutor.Shareghi Najar, Amir January 2014 (has links)
Empirical studies have shown that learning from worked examples is an effective learning strategy. A worked example provides step-by-step explanations of how a problem is solved. Many studies have compared learning from examples to unsupported problem solving, and suggested presenting worked examples to students in the initial stages of learning, followed by problem solving once students have acquired enough knowledge. Recently, researchers have started comparing learning from examples to supported problem solving in Intelligent Tutoring Systems (ITSs). ITSs provide multiple levels of assistance to students, adaptive feedback being one of them. The goal of this research is to investigate using examples in constraint-based tutors by adding examples into SQL-Tutor. SQL-Tutor is a constraint-based tutor that teaches the Structured Query Language (SQL). Students with different prior knowledge benefit differently from studying examples; thus, another goal of the research is to propose an adaptive model that considers the student’s prior knowledge for providing worked examples.
Evaluation of this research produced promising results. First, a fixed sequence of alternating examples and problems was compared with problems only and examples only. The result shows that alternating examples and problems is superior to the other two conditions. Then, a study was conducted, in which a fixed sequence of alternating worked examples and tutored problem solving is compared with a strategy that adapts the assistance level to students’ needs. The adaptive strategy determines the type of the task (a worked example, a faded example or a problem to be solved) based on how much assistance the student received in the previous problem. The results show that students in the adaptive condition learnt significantly more than their peers who were presented with the fixed sequence of worked examples and problem solving. The final study employed eye tracking and demonstrated that novices and advanced students study SQL examples differently. Such information can be used to provide proactive rather than reactive feedback messages to students’ actions.
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Semi-Automatic assessment of students' graph-based diagramsBatmaz, Firat January 2011 (has links)
Diagrams are increasingly used in many design methods, and are being taught in a variety of contexts in higher education such as database conceptual design or software design in computer science. They are an important part of many assessments. Currently computer aided assessments are widely used for multiple choice questions. They lack the ability to assess a student's knowledge in a more comprehensive way, which is required for diagram-type student work. The aim of this research is to develop a semi-automatic assessment framework, which enables the use of computer to support the assessment process of diagrammatic solutions, with the focus of ensuring the consistency of grades and feedback on solutions. A novel trace model, that captures design traces of student solutions, was developed as a part of the framework and was used to provide the matching criteria for grouping the solutions. A new marking style, partial marking, was developed to mark these solution groups manually. The Case-Based Reasoning method is utilised in the framework to mark some of the groups automatically. A guideline for scenario writing was proposed to increase the efficiency of automatic marking. A prototype diagram editor, a marking tool and scenario writing environment were implemented for the proposed framework in order to demonstrate proof of concept. The results of experiments show that the framework is feasible to use in the formative assessment and it provides consistent marking and personalised feedback to the students. The framework also has the potential to significantly reduce the time and effort required by the examiner to mark student diagrams. Although the constructed framework was specifically used for the assessment of database diagrams, the framework is generic enough to be used for other types of graph-based diagram.
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Accompagnement du changement individuel et collectif par le développement des compétences / Support of the individual and collective change by the development of the skillsDenancé, Victor 07 July 2017 (has links)
La présente thèse a pour objet l'étude de l'appropriation de nouvelles pratiques au sein des organisations. Cette problématique est abordée par le prisme des processus psychologiques développementaux, cognitifs et sociaux en jeu dans le développement des compétences des acteurs. Notre réflexion théorique nous amène à présenter les travaux précurseurs lewiniens, quelques modèles significatifs du changement organisationnel et de l'apprentissage organisationnel, puis un modèle d'analyse des compétences permettant de décrire les schèmes d'activité des acteurs en matière d'invariants opératoires (i.e., ce qui est tenu pour vrai ou pertinent) et de règles d'action (i.e., actions effectrices sur l'environnement). La mise en place d'une série d'études expérimentales nous permet de conclure que le développement des compétences individuelles et collectives est facilité lorsque le dispositif d'apprentissage permet aux acteurs d'associer la conceptualisation des invariants opératoires à la production des règles d'action. Ces résultats sont expliqués principalement au regard du concept piagétien de prise de conscience. Les contributions et limites de la thèse sont finalement discutées. / This thesis focuses on the appropriation of new practices within organizations. This topic is analyzed through the lens of the developmental, cognitive and social psychological processes involved in the development of stakeholders' competencies. Our theoretical discussion presents the Lewinian approach to change management, several significant organizational change and organizational learning models, as well as a model of competencies analysis that breaks down stakeholder's activity schemes into operational invariants (i.e., what is held for true or relevant) and action rules (i.e., actions effecting the environment). A series of experimental studies reveals that the development of individual and collective competencies is facilitated when the learning material allows stakeholders to link the conceptualization of operational invariants to the production of action rules. These results are mostly explained in terms of the Piagetian concept of awareness. The contributions and limits of the thesis are finally discusse
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Learning with Multimedia: Are Visual Cues and Self-Explanation Prompts Effective?January 2011 (has links)
abstract: The purpose of this study was to investigate the impacts of visual cues and different types of self-explanation prompts on learning, cognitive load and intrinsic motivation, as well as the potential interaction between the two factors in a multimedia environment that was designed to deliver a computer-based lesson about the human cardiovascular system. A total of 126 college students were randomly assigned in equal numbers (N = 21) to one of the six experimental conditions in a 2 X 3 factorial design with visual cueing (visual cues vs. no cues) and type of self-explanation prompts (prediction prompts vs. reflection prompts vs. no prompts) as the between-subjects factors. They completed a pretest, subjective cognitive load questions, intrinsic motivation questions, and a posttest during the course of the experience. A subsample (49 out of 126) of the participants' eye movements were tracked by an eye tracker. The results revealed that (a) participants presented with visually cued animations had significantly higher learning outcome scores than their peers who viewed uncued animations; and (b) cognitive load and intrinsic motivation had different impacts on learning in multimedia due to the moderation effect of visual cueing. There were no other significant findings in terms of learning outcomes, cognitive load, intrinsic motivation, and eye movements. Limitations, implications and future directions are discussed within the framework of cognitive load theory, cognitive theory of multimedia learning and cognitive-affective theory of learning with media. / Dissertation/Thesis / Ph.D. Educational Technology 2011
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Quality of Human-Computer Interaction : Self-Explanatory User Interfaces by Model-Driven Engineering / Qualité de l'interaction homme machine : interfaces auto-explicatives par ingénierie dirigée par les modèlesGarcia Frey, Alfonso 03 July 2013 (has links)
En Interaction Homme-Machine, la qualité est une utopie : malgré toutes les précautions prises en conception, il existe toujours des utilisateurs et des situations d'usage pour lesquels l'Interface Homme-Machine (IHM) est imparfaite. Cette thèse explore l'auto-explication des IHM pour améliorer la qualité perçue par les utilisateurs. L'approche s'inscrit dans une Ingénierie Dirigée par les Modèles. Elle consiste à embarquer à l'exécution les modèles de conception pour dynamiquement augmenter l'IHM d'un ensemble de questions et de réponses. Les questions peuvent être relatives à l'utilisation de l'IHM (par exemple, "A quoi sert ce bouton ?", "Pourquoi telle action n'est pas possible ?) et à sa justification (par exemple, "Pourquoi les items ne sont-ils pas rangés par ordre alphabétique ?"). Cette thèse propose une infrastructure logicielle UsiExplain basée sur les méta-modèles UsiXML. L'évaluation sur un cas d'étude d'achat de voitures montre que l'approche est pertinente pour les questions d'utilisation de l'IHM. Elle ouvre des perspectives en justification de conception. / In Human-Computer Interaction, quality is an utopia. Despite all the design efforts, there are always uses and situations for which the user interface is not perfect. This thesis investigates self-explanatory user interfaces for improving the quality perceived by end users. The approach follows the principles of model-driven engineering. It consists in keeping the design models at runtime so that to dynamically enrich the user interface with a set of possible questions and answers. The questions are related to usage (for instance, "What's the purpose of this button?", "Why is this action not possible"?) as well as to design rationale (for instance, "Why are the items not alphabetically ordered?"). This thesis proposes a software infrastructure UsiExplain based on the UsiXML metamodels. An evaluation conducted on a case study related to a car shopping webiste confirms that the approach is relevant especially for usage questions. Design rationale will be further explored in the future.STAR
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