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IDT 873 Abstract: Design Based Research Jennifer Maddrell Wang, F., & Hannafin, M. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development, 53(4), 5-23. doi: 10.1007/BF02504682. Overview Wang and Hannafin (2005) review theory and practice of design-based research (DBR), which fosters concurrent design, research, and practice, as a methodology for technologyenhanced learning environments (TELEs). Following a review of proposed models, Wang and Hannafin suggest DBR’s iterative, participative and situated processes as a means of forwarding instructional design research, theory, and practice. Definition and Characteristics Wang and Hannafin assess the various conceptions of DBR, including design experiments, design research, development research, and formative research. Given the varied emphasis across these conceptions, Wang and Hannifin offer a working definition of DBR within their paper, including “a systematic but flexible methodology aimed to improve educational practices through iterative analysis, design, development and implementation, based on collaboration among researchers and practitioners in real-world settings, and leading to a contextually-sensitive design principles and theories.” Their conception of DBR includes five key characteristics, including being (a) pragmatic (linking theory, research, and practice), (b) grounded (anchored in theories of learning and instruction, as well as real-world contexts) (c) interactive / iterative / flexible between researchers, designers, and practitioners, (d) integrative (blending a host of analysis and evaluation methods), and (e) contextual (localized results linked to prior observations and articulated in the form of heuristics to advance both theory and practice). Heuristics for Designers and Researchers Wang and Hannifin offer DBR principles which parallel many traditional ID activities, including formative and summative evaluation practices. A key distinction between ID evaluation and DBR is the eye toward theory development and the forwarding of generalizable, yet contextually influenced, design principles. However, the incorporation of theory development goals shifts the focus of the traditional ID evaluation approach. Instructional design plans do not have theory development as a central goal which may significantly alter the scope and methodology of the instructional design and evaluation process. The added time to collect and analyze data may interfere with the goal of ID efficiency. Critique An intriguing element of DBR is the synergy of research and instructional design practice within real-world instructional settings. DBR offers a means of placing the instructional design evaluation of a single intervention within a broader context of prior similar evaluations. However, a risk of a DBR approach is the “look what I did last summer” report of localized findings. Therefore, the ability to ground the evaluated instruction in prior theory and research and to offer valid findings which are generalizable beyond the specific instructional setting seems central to the DBR versus traditional research debate. Wang and Hannafin frame this within a discussion of meta-design knowledge and context-based knowledge which they note must transcend the specific design. Submitted: November 20, 2008

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Concept Learning and Instruction Running head: CONCEPT LEARNING AND INSTRUCTION 1 Concept Learning and Instruction Jennifer Maddrell Old Dominion University IDT 873 Advanced Instructional Design Techniques Dr. Gary Morrison November 12, 2008 Concept Learning and Instruction 2 Concept Learning and Instruction While concept learning has been considered across a broad spectrum of theoretical foundations, the prescriptions for instruction are strikingly similar. A rich history of research in concept learning and instruction has led to empirically based instructional design strategies which focus on (a) defining and presenting a concept’s attributes, (b) creating and presenting instances of examples and non-examples of the concept, and (c) fostering guided learner practice in attribute isolation, instance discrimination and generalization, and concept use. This paper offers a summary the central views on the nature of concepts, concept learning measurement, and concept instruction based on a survey of concept learning and instruction theory and research. The Nature of Concepts Whether viewed as the object of learning or a building block to more meaningful learning, there is general agreement regarding the concept construct. Markle and Tiemann (1970, p. 52) considered the similarity in the conception of concepts across theorists to be “remarkable.” A concept is generally described as a category (class, group, or set) of objects, events, symbols, or relationships with shared characteristics or properties, often referred to as attributes (Tennyson & Cocchiarella, 1986). A category is often described as a grouping of objects, events, symbols, or relationships while an attribute describes the dimension from which the objects and events differ (Brown, 1958). Further, membership to the category is generally considered based on either the perceived physical attributes (concrete concepts) or solely by definition (abstract concepts) (Smith & Ragan, 1999). Concept Learning Measurement While the theoretical perspectives vary regarding how concept learning occurs, there is noteworthy similarity in how concept learning, also referred to as concept attainment or acquisition, is measured. Concept learning is generally deemed to have occurred when the learner is able to discriminate among attributes of a concept and to evaluate new examples based on membership to the concept category (Klausmeier & Feldman, 1975). Based on the terminal objective of the instruction, concept learning and assessment can focus on both recall and application of the to-be-learned concept (Morrison, Ross, & Kemp, 2001). The following examines the role of attribute isolation, instance discrimination and generalization, and conceptsin-use in measuring concept learning. Attribute Isolation Concept learning assessment typically focuses on a learner’s ability to consider the nature of instances encountered based upon defining attributes belonging to the concept category (Bruner, Goodnow, & Austin, 1956). A common focus in concept learning assessment is the learner’s ability to discern the relevant criteria by which attributes are grouped into the concept categories (Joyce & Weil, 1972). In measuring concept attainment, two types of attributes are of concern, including (a) defining attributes and (b) criterial attributes isolated by the learner (Bruner et al., 1956). Defining attributes reflect the standard criteria set by appearance or convention. In contrast, criterial attributes are established by the individual to assess and judge membership in the category. Concept learning (or attainment), therefore, is judged based the extent to which the criterial attributes isolated by the learner match the defining attributes. Instance Discrimination and Generalization Concept learning assessment also centers on a learner’s ability to (a) discriminate between what is and what is not a member of the class and (b) generalize new examples by appropriately judging instances based on the degree of membership to the exemplar class (Markle, 1969). Therefore, successful concept learning is assessed based on the learner’s ability Concept Learning and Instruction 3 to place instances in the exemplar class and to respond to members of the exemplar class as a whole (Gagné, 1965). To do so, learners must be able to discriminate non-members from members of the class while not overgeneralizing (incorrectly judging non-examples as examples) or undergeneralizing (incorrectly judging examples as non-examples) (Markle & Tiemann, 1970). Concepts-in-Use In a recent review of theory and research on the role of concepts in learning and instruction, Jonassen (2006) argued that the historical focus of concept learning has been on concept attainment as a discrete and terminal learning outcome without regard to where the concept fits within a larger conceptual framework. In contrast, Jonassen suggested a focus on concepts-in-use in which concept learning centers on concepts as mental model building blocks. As such, Jonassen argues that the instruction and assessment should shift beyond the learner’s ability to identify, discriminate, and generalize membership based on concept attributes and examples to how the learned concepts are organized within the learner’s overall conceptual framework. He asserts that concept learning and assessment should focus on the learner’s ability to describe or represent conceptual patterns and propositions, as in concept maps, word associations, and model building. While Jonassen (2006) may be correct in advocating an expanded instructional focus and a more meaningful terminal objective, it does not follow from his argument that prior concept learning prescriptions do not lead to the learner’s ability to demonstrate application of the concept. Beyond assessing the learner’s ability to correctly identify or categorize concepts, countless other means have been suggested to measure the learner’s ability to use and apply the concept, to make judgments and arguments on the basis of the concept, and to infer membership in superordinate categories (Tessmer, Wilson, & Driscoll, 1990). Therefore, instead of a call for abandonment of past instructional prescriptions, a call for enhanced practice and assessment which forces more meaningful learner application of the to-be-learned concept may be more compelling. Concept Instruction The similarity across theoretical foundations that has been described thus far continues across a review of concept teaching models regarding instructional presentation, learner practice, and guidance. Concept instruction typically includes presentation of a concept definition, presentation of sample instances, and practice in classifying instances of examples and nonexamples (Tennyson & Cocchiarella, 1986). While some differences exist along behavioral, cognitive, or social-cognitive theoretical lines, the prescriptions for presentation, learner practice and guidance cannot be contrasted purely on differences in theoretical foundation. Instead, the prescriptions across theoretical foundations are quite similar with differences occurring in areas such as sequencing, the degree of learner autonomy to discover attributes and instances, and the terminal objective of the lesson. In general, instructional strategy differences can be seen as either expository (direct presentation of attributes and instances) approaches inquiry (learner exportation or discovery of attributes and instances) approaches or (Smith & Ragan, 1999). Setting aside an analysis of the various media and instructional delivery alternatives, the following highlights common presentation, learner practice, and learner guidance techniques stemming from a variety of inquiry and expository approaches. Concept Learning and Instruction 4 Defining Concept Attributes Research suggests that learning is enhanced when a concrete definition is presented and that a definition alone is roughly as effective as a single set of examples and non-examples (Klausmeier & Feldman, 1975). Therefore, concept instruction generally includes providing learners with a stated definition of the domain of the concept based on the properties (attributes) of the concept class (Markle, 1975). Some advocate that the concept definition should identify the name of the concept, the attributes, and how the attributes are combined to determine class membership (Merrill & Tennyson, 1977). When attributes are defined and presented, their characteristics are typically considered based on their function and the degree to which they vary, can be observed, and relate to one another. A critical attribute refers to the necessary characteristics for determining membership while variable attributes are characteristics shared by some members of the class, but are not necessary for class membership (Merrill & Tennyson). Attribute characteristics that are stable across contexts are of constant-dimension while those that vary or change are of variable-dimension (Tennyson & Cocchiarella, 1986). Some suggest further defining attributes based on their (a) intrinsic prosperities, referring to their observable and invariant properties, (b) functional properties, referring to how something functions or is used, or (c) relational properties, referring to the invariant relationship between items. (Klausmeier, 1992). When defined based on their relational properties, concepts fall within three categories, including (a) conjunctive concepts which are defined by one attribute and another, (b) disjunctive concepts which are defined by one attribute or another, and (c) relational concepts which are defined by a relationship between attributes (Fleming & Levie, 1978) Creating Instances Research suggests that factors such as the number, categorization, type, and range of instances presented to learners influence concept learning. Instances refer to examples and nonexamples of the concept being considered and, depending upon whether the concept is physical or abstract, can take the form of (a) a referent or actual object, (b) an isomorphic representation or model of the object, or (c) a symbolic representation including words or other symbols (Merrill & Tennyson, 1977). It is generally suggested that designers augment the presentation of the concept definition with multiple rational sets of examples and non-examples (Markle, 1969). Others suggest that a wide variety of examples be included (Fleming & Levie, 1978) and that the set of example and non-example instances should be matched (Merrill & Tennyson, 1977). Markle (1969 and 1975) offers a standard case concept analysis which focuses on the creation of a rational set of examples and non-examples to be used in both instruction and testing that involves (a) the identification of both critical and variable attributes (b) creation of examples in which all of the critical attributes are present, and (c) creation of non-examples. The ideal non-example is suggested to be one that shares all but one critical property with the concept class and is as concrete as possible (Markle & Tiemann, 1970). In contrast to presentation of sets of examples and non-examples, others suggest presentation of prototypical examples (Tennyson & Cocchiarella, 1986). An alternate view from the previously stated exemplar perspective, the prototype viewpoint suggests that a concept is encoded in memory as a prototypical example of a category member (Klausmeier, 1992). The prototype (or central example) is deemed to be constructed based on the learner’s experiences with examples of the class (Tessmer et al., 1990). Concept Learning and Instruction 5 Presentation, Learner Practice, and Guidance Presenting the concept label and attribute definition. Research suggests that presentation of concept labels and definitions assists learners in concept attainment by establishing the dimensions and boundaries of the learning task (Tennyson & Cocchiarella, 1986). Some argue that a definition of the concept focusing on the critical (defining) attributes should be presented prior to the presentation of instances of examples and non-examples (Tennyson & Park, 1980). Such an approach is often referred to as a RULEG approach in which, rules, principles, generalizations, or definitions (RU) are presented prior to examples (EG) (Markle, 1969). Others suggest beginning with presentation of the definition followed quickly by a recall or recognition activity (Merrill & Tennyson, 1977). However, others advocate an EGRUL presentation sequence in which the example is first presented followed by the rule, especially in cases where the concept is difficult or abstract (Fleming & Levie, 1978). As part of an inquiry approach, others suggest beginning with instructional activities that encourage learners to speculate about the defining attributes based on presentation of examples and non-examples (Joyce & Weil, 1972). Overall, while some variations in approach exist across the reviewed models, early initial presentation or discovery of the concept label and attribute definition is generally advocated. Presenting instances. While the emphasis and sequencing of instance presentation varies across models, the presentation of some form of instance was present in every reviewed concept teaching strategy. As noted, rarely in the reviewed models was an EGRUL approach described in which presentation of examples preceded the definition. Again, an EGRUL approach is generally suggested as a strategy when the concept is difficult or abstract and the learner may not have experience with examples of the concept. Presentation of instances tends to fall along two lines, either (a) presentation of sets of examples and non-examples or (c) presentation of prototypical examples. Some deemphasize the prescription for expository presentation of instance examples and non-examples, but advocate an inquiry approach in which data or information about the concept is presented to the learner from which the learner is able to draw inferences about the concept’s attributes (Joyce & Weil, 1972) In contrast, some advocate incorporating presentation of carefully selected example and non-example instances within either expository or inquiry presentation (Merrill & Tennyson, 1977). In expository presentation, the instance is presented, often highlighting or isolating critical attributes, which does not require a response from the learner. This is in contrast to inquiry approach where learners are presented with either an example or non-example and then asked to immediately identify whether it is a member of the concept category. Others favor the use of prototypical example presentation and suggest presenting learners with the best example of the typical class, followed by expository and interrogatory examples and non-examples (Tennyson & Cocchiarella, 1986). Research suggests that presentation of a best example forms a prototype for the learner and the additional examples provide elaboration of key dimensions of the prototype (Park, 1984). Some advocate a modified approach in which learners are offered various transformations of the instance which lead to a best example (Jacob, Deming, & Walbesser, 1976). However, most suggest that a single example is not sufficient and that a range of examples is needed (Markle, 1969). This view is supported by research that suggests an advantage for presenting additional rational sets of examples and non-examples over a single set (Klausmeier & Feldman, 1975). Yet, research also indicates the importance of modifying Concept Learning and Instruction 6 instance presentation based on learner mastery as instance presentation after the learner has achieved mastery may result in the learner losing interest (Tennyson & Rothen, 1977). Guiding Learner Practice. As discussed previously, instructional can lead to either learner recall or application of the to-be-learned concept. A common approach geared toward recall is to offer learners various practice opportunities to classify new instance as members or nonmembers of the class followed by corrective guidance. As noted, this typically takes the form of rule presentation and example presentation which is followed by learner practice and instructional guidance indicating either a correct or incorrect learner classification of the concept (Merrill & Tennyson, 1977). In addition, a host of inquiry and generative approaches are recommended which are often geared toward learner application of the concept, including the previously mentioned model building exercises. Concept mapping, as a form of model building, can assist learners to not only organize definitions and examples, but also to infer relationships within a larger conceptual framework (Tessmer et al., 1990). Some view model building as an ideal practice and guidance strategy for concept learning as models require learners to externalize their understanding of not only the concept, but also conceptual relationships (Jonassen, Strobel, & Gottdenker, 2005). Summary Heuristics for Designers As discussed, research in concept learning and instruction across a spectrum of theoretical foundations has led to empirically based instructional design heuristics which focus on (a) defining and presenting a concept’s attributes, (b) creating and presenting instances of examples and non-examples of the concept, and (c) fostering guided learner practice in attribute isolation, instance discrimination and generalization, and concept use. Within this common framework, differences in strategy can be viewed as either expository approaches where the instruction offers direct presentation of attributes and instances or inquiry approaches where the learner is offered opportunities to explore or discover relevant attributes and instances. As a summary of heuristics for designers, the following highlights common presentation, learner practice, and learner guidance techniques stemming from a variety of inquiry and expository approaches: 1. Define the concept. Prepare a concept definition which focuses on attributes of the concept. In doing so, consider the critical attributes that are necessary characteristics for determining membership, as well as the variable attributes which are shared by only some in the concept category. When defining the concept, it is helpful to consider whether it is a conjunctive concept that can be defined by one attribute and another, a disjunctive concept which is defined by one attribute or another, or a relational concept which is defined by a relationship between attributes. 2. Create instances. Create instances for presentation to the learner including examples in which all of the critical attributes are present and non-examples in which all but one critical property is present. Consider also the prototypical example. Depending upon the type of concept, the instances may be a referent or actual object, an isomorphic representation or model of the object, or a symbolic representation including words or other symbols. 3. Design presentation and guided practice opportunities. Incorporate presentation and guided learner practice opportunities which lead to not only recall, but also application of the concept within a larger conceptual framework. Consider using a RULEG approach in which the definitions (RU) are presented prior to examples (EG), unless the concept is Concept Learning and Instruction 7 difficult or abstract in which the EGRUL approach may be more appropriate. When assessing at a recall level, offer learners the opportunity to classify new instance as members or nonmembers of the class followed by corrective guidance. When assessing at an application level, include practice and guidance approaches which require the learner to use the concept. Such exercises might include asking the learner to make arguments or judgments on the basis of the concept or to infer relationship or membership by creating a concept map. Concept Learning and Instruction 8 References Brown, R. (1958). Words and things. Glencoe, Ill.: The Free Press. Bruner, J. S., Goodnow, J., & Austin, G. A. (1956). A Study of Thinking, A Wiley publication in psychology. (p. 330). New York, Wiley. Fleming, M. L., & Levie, W. H. (1978). Instructional message design : principles from the behavioral sciences. Englewood Cliffs, N.J.: Educational Technology Publications. Gagné, R. M. (1965). The Conditions of Learning. New York, Holt, Rinehart and Winston. Jacob, S. H., Deming, B. S., & Walbesser, H. H. (1976). They Too Teach Concepts. Educational Researcher, 5(1), 15-16. Jonassen, D. (2006). On the Role of Concepts in Learning and Instructional Design. Educational Technology Research and Development, 54(2), 177-196. Jonassen, D., Strobel, J., & Gottdenker, J. (2005). Model building for conceptual change. Interactive Learning Environments, 13(1/2), 15-37. Joyce, B. R., & Weil, M. (1972). Models of Teaching (p. 402). Englewood Cliffs, N.J., PrenticeHall. Klausmeier, H. J. (1992). Concept Learning and Concept Teaching. Educational Psychologist, 27(3), 267. Klausmeier, H. J., & Feldman, K. V. (1975). Effects of a definition and a varying number of examples and nonexamples on concept attainment. Journal of Educational Psychology, 67(2), 174-178. Markle, S. M. (1969). Good Frames and Bad; a Grammar of Frame Writing. New York, Wiley. Markle, S. M. (1975). They Teach Concepts, Don't They? Educational Researcher, 4(6), 3-9. Markle, S. M., & Tiemann, P. W. (1970). Problems of Conceptual Learning. Journal of Educational Technology, 1(1). Merrill, M. D., & Tennyson, R. D. (1977). Teaching Concepts: An Instructional Design Guide (p. 213). Englewood Cliffs, N.J.: Educational Technology Publications. Morrison, G. R., Ross, S. M., & Kemp, J. E. (2001). Designing effective instruction (3rd ed.). New York: John Wiley & Sons, Inc. Park, O. (1984). Example Comparison Strategy versus Attribute Identification Strategy in Concept Learning. American Educational Research Journal, 21(1), 145-162. Smith, P. L., & Ragan, T. J. (1999). Instructional design. New York: Wiley. Tennyson, R. D., & Cocchiarella, M. J. (1986). An Empirically Based Instructional Design Theory for Teaching Concepts. Review of Educational Research, 56(1), 40-71. Tennyson, R. D., & Park, O. (1980). The Teaching of Concepts: A Review of Instructional Design Research Literature. Review of Educational Research, 50(1), 55-70. Tennyson, R. D., & Rothen, W. (1977). Pretask and on-task adaptive design strategies for selecting number of instances in concept acquisition. Journal of Educational Psychology, 69(5), 586-592. Tessmer, M., Wilson, B., & Driscoll, M. (1990). A new model of concept teaching and learning. Educational Technology Research and Development, 38(1), 45-53.

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IDT 873 Abstracts: Feedback Jennifer Maddrell Olina, Z., & Sullivan, H. (2004). Student self-evaluation, teacher evaluation, and learner performance. Educational Technology Research and Development, 52(3), Research Purpose and focus. Olina and Sullivan (2004) examined the effect of student selfevaluation and teacher feedback on learning. Their research focused on the comparative and combined performance effects of self- and teacher-evaluation, as well as the effect of both on student and teacher attitudes. Olina and Sullivan predicted that teacher evaluation would improve student performance to a greater extent that self-evaluation. Further, they predicted that selfevaluation would result in better performance and engagement than no-evaluation. Methodology. 341 high school students in Latvia took part in the study. Learners came from 16 classes which were selected from eight schools in different Latvian regions, including a diverse mix of rural and urban areas and of socio-economic backgrounds. Each of the eight schools were stratified based on ability (based on ninth grade standardized Latvian exams) and grouped into either the four higher or four lower ability schools. Each of the four schools in each group were then randomly assigned to one of four treatment groups, including (a) no evaluation, (b) self-evaluation, (c) teacher-evaluation, and (d) self-plus-teacher evaluation groups.. Eight teachers taught two classes each. Over the course of a six week term consisting of two 40 minute class periods per week, all students took the same 12 lesson instructional program about experimental research design which included both a student book and teacher guide. Students in all classes conducted the same experiments, produced written reports as required by the instruction, and were introduced to the project rating scale, a descriptive rubric for evaluating the written projects. However, students in the self-evaluation group formally selfevaluated their own work based on the project rating scale. Students in the teacher-evaluation group were provided written feedback from their teachers based on the same project rating scale. Students in the self-plus-teacher group formally self-evaluated their own work and received written teacher feedback. Students in the no-evaluation (control) group received no formal feedback from the teacher and they were not asked to formally evaluate their own work. Performance measures included ratings of the students’ final projects and posttest scores. In addition, student and teacher attitudes were measured in surveys after the course. Results and conclusions. While there were no significant differences between treatment groups on the posttest scores, the teacher-evaluation and self-plus-teacher groups had significantly higher project scores than the no evaluation group and the self-evaluation groups. Further, in both self-evaluation groups, over 90% of students rated their projects higher than the experimenter-based rating in the final projects. Students in both groups with formal selfevaluation reported more positive attitudes toward the program as compared to the other groups, but both students and teachers preferred teacher-evaluation and felt it provided a more valuable evaluation. Heuristics The results of these experiments suggest that incorporating formal self-evaluation may increase a learner’s confidence in his or her future performance. However, teacher-evaluation alone or combined with self-evaluation is more likely to improve learner performance over no evaluation or self-evaluation alone. Page | 1 Submitted 20081104 IDT 873 Abstracts: Feedback Jennifer Maddrell Critique This study, conducted over a six week term, provides support for prior research that suggests teacher feedback improves student performance. While no significant differences were found in posttest measures, the results suggest that teacher feedback may provide superior learning outcomes (based on other than test application measures) as compared to no evaluation feedback or self-evaluation feedback. Yet, the results do indicate value in learner self-evaluation in terms of increased learner self-control and self-confidence. Page | 2 Submitted 20081104

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IDT 873 Abstracts: Attitudes Jennifer Maddrell Kardash, C. M., & Scholes, R. J. (1995). Effects of Preexisting Beliefs and Repeated Readings on Belief Change, Comprehension, and Recall of Persuasive Text. Contemporary Educational Psychology, 20(2), 201-221. Research Purpose and focus. Kardash and Scholes (1995) examined how preexisting beliefs interacted with reading of persuasive test to influence information recall and belief change. Citing prior research that suggest preexisting attitudes and beliefs influence how evidence is evaluated, Kardash and Scholes predicted that subjects whose preexisting beliefs and attitudes were consistent with the presented text would recall more causal explanations within the text, as well as more information overall. In addition, they predicted that those who read the text twice would remember more information than those who read the text only once. Finally, they predicted that the persuasive text would influence all subjects, but to a greater extent in those whose preexisting beliefs and attitudes were consistent with the text. Methodology. 61 undergraduate students enrolled in an educational psychology class received credit for their participation in this study. The students were randomly assigned to one of two treatment groups, including (a) a one-read, or (b) a two-read group. Entry beliefs were measured based on 9-point Likert-type scale assessment of the extent to which subjects agreed or disagreed with a variety of offered causes of how AIDS could be transmitted. Post-treatment beliefs were similarly measured. All learners reviewed the same 1,195 word text based passage about causes of AIDS. Both groups returned two days later. Those in the one-read group completed an unrelated exercise while the two-read group read the exact passage a second time. Time spent reading the text was measured in both sessions. One week later, all subject returned for a free recall text and the post-beliefs test. Results and conclusions. Results supported the prediction that beliefs about the controversial topic effect what is recalled about a persuasive text on the topic. Those with beliefs consistent with the text remembered marginally more causal, as well as less central information than those with less consistent entry beliefs. In addition, causal arguments promoted belief change in all subjects, but more so for those with similar preexisting beliefs to the text. Finally, contrary to predictions, the repeated reading did not influence the overall amount or type of information recalled. Heuristics The results of these experiments suggest that a learner’s entry beliefs and attitudes about causal information regarding a controversial topic may influence how the learner recalls and is persuaded by the to-be-learned material. If the information is consistent with entry beliefs, the learner may be more likely to recall or be persuaded by the material than those with entry beliefs that are inconsistent with the presented instructional material. Critique This study provides support for prior research that suggests preexisting beliefs serve as a schema which influences how new persuasive information will impact belief change and recall. Yet, as noted by the authors, this study focused on the subjects’ beliefs about causes of AIDS, not Page | 1 Submitted 20081114 IDT 873 Abstracts: Attitudes Jennifer Maddrell their attitudes towards AIDS and those with AIDS which may or may not influence the reported results. Brannon, L. A., Tagler, M. J., & Eagly, A. H. (2007). The moderating role of attitude strength in selective exposure to information. Journal of Experimental Social Psychology, 43(4), 611-617. Research Purpose and focus. Brannon, Tagler, and Eagly (2007) examined whether attitude strength influences information selection. Citing prior research that suggests people seek out and prefer to receive information that is consistent with their attitudes, Brannon, Tagler, and Eagly predicted that selective exposure would be more pronounced in those with more strongly held attitudes than for those with weakly held attitudes. Methodology. In a series of three studies following roughly the same methodology as the first, their prediction was tested. In the first study, 270 students enrolled in an undergraduate psychology program were recruited to participate. They were randomly assigned to one of two treatment groups, including (a) a one read, or (b) a two-read group. Entry attitudes toward social issues were measured based on a questionnaire that assessed attitude position and strength regarding social issues. Participants’ attitude positions were measured on a 7-point scale. Attitude strength was also measured on a 7-point scale assessing how important the issue was, how sure they were of their position, how central their attitudes were to their self-concepts, how likely they were to change their attitudes, and how much knowledge they possessed on the issue. Several weeks after completing the entry questionnaire, participants engaged in a selective exposure task in which they reviewed a list of ten article titles and abstracts containing two opposite stances toward five difference social issues. For each article, the participants ranked on a 9-point scale how desirable it would be for them to read the article. The participant’s choice of either an attitudinally consistent or inconsistent selection was then measured. Results and conclusions. Results supported the prediction that attitude strength relates to selective exposure. Stronger attitudes were associated with increased preference for attitudinally consistent article titles. Heuristics The results of these experiments suggest that the strength of the learner’s entry attitudes about a topic may influence what information the learner selects on the topic. If the learner has strongly held attitudes on a topic, he or she may seek out information that is consistent with their entry attitudes. Critique This study provides support for prior research that suggests preexisting attitudes influence information selection. These research findings have important implications in instructional settings where learners are free to select instructional content. If learners are less inclined to select material that is in opposition to their entry attitudes, will they select Page | 2 Submitted 20081114 IDT 873 Abstracts: Attitudes Jennifer Maddrell information that gives a balanced perspective on the topic? Given the potential for attitudinally influenced selection, should learning material selection be under the direction of the instructor? Also, how does instructor’s or instructional designer’s entry attitude influence selection of material for a class? Page | 3 Submitted 20081114

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IDT 873 Abstracts: Problem Solving Jennifer Maddrell Atkinson, R. K., Renkl, A., & Merrill, M. M. (2003). Transitioning From Studying Examples to Solving Problems: Effects of Self-Explanation Prompts and Fading Worked-Out Steps. Journal of Educational Psychology, 95(4), 774-783. Research Purpose and focus. Atkinson, Renkl, and Merrill (2003) examined the impact of fading and selfexplanation prompts on problem solving. Two separate experiments were conducted. While the second was performed after the results from the first were known, the purpose was to replicate the experiment in a more authentic setting. The three primary research questions focused on whether or not (a) backward fading (BF) results in better learning outcomes than exampleproblem (EP) pairs, (b) self-explanation prompts lead to better outcomes, and (c) an advantage exists when using both fading and self-explanation prompts. Methodology. In the first study, 78 undergraduate students took part in the 90 minute lab based study. In the second study, 40 highs school students volunteered to participate within their high school. In the first study, the students were randomly assigned to one of four treatment groups, including (a) BF only (worked examples in which all problem solutions are sequentially provided to the learner, but solution steps are gradually eliminated on each subsequent worked examples), (b) EP pairs only (worked examples followed by a problem-solving task), (c) BF plus prompting (BF condition with self-explanation prompts), and (d) EP pairs plus prompting (EP condition with self-explanation prompts). The second study did not include the EP pairs only or EP pairs plus prompting conditions. Otherwise, the instruments, scoring, and procedures for both studies were identical. The instructional treatment for all of the groups was conducted via a computer-based learning tool and involved probability word problems. The instruction included sets of worked examples and problems which ran in one of four modes; one mode for each noted condition, as described above. A demographic questionnaire and pretest to assess prior knowledge were conducted before the treatment. A posttest was administered at the conclusion of the session. In addition, time on task during the lesson was recorded. Results and conclusions. With regard to the original research questions, the research findings from the first experiment suggest that (a) backward fading resulted in better learning outcomes than the example-problem pairs, (b) self-explanation prompts led to better learning outcomes, but (c) there was no apparently advantage from the use of fading and self-explanation prompts. The results of the second study support the finding that self-explanation prompts with a backward fading example sequence supports learning in a time effective manner. Heuristics The results of these experiments suggest that instruction should incorporate a fading technique in which the problem solutions within worked examples are initially fully provided to the learner, but the solution steps are gradually eliminated as the learner’s skill development increases until only independent problem solving practice is utilized in the later stages of instruction. Further, the findings suggest that learning effectiveness and efficiency may be enhanced when this fading approach is combined with self-explanation prompting in which the learner is asked to consider the underlying principle(s) applicable to the problem. Critique In this study, the findings build on prior research on fading (from worked example study to problem solving) that suggests the importance of fading the solution steps in worked examples and progressing to independent problem solving as the learner’s skill level improves. In addition, Page | 1 Submitted 20081030 IDT 873 Abstracts: Problem Solving Jennifer Maddrell the study furthers research on the self-explanation effect which suggests that learning is enhanced when learners are prompted to select the underlying principles during problem solving. The researchers suggest these findings provide support for the importance of feedback following learner self-explanations. However, as noted by the researchers, it would be interesting to further explore the effect of providing feedback to learner self-explanations in less structured domains that the one studied here. In other words, what would be the outcome in domains where the principles involved in problem solving are less clear or less restricted? van Gog, T., Paas, F., & van Merrienboer, J. (2008). Effects of studying sequences of processoriented and product-oriented worked examples on troubleshooting transfer efficiency. Learning and Instruction, 18(3), 211-222. Research Purpose and focus. van Gog, Paas, and van Merrienboer (2008) evaluate the effect of process-oriented worked examples which include the rationale behind the presented solution comparing their use to product-oriented worked examples at both the beginning of training and at later stages. The purpose of the described study was to evaluate whether or not processoriented worked examples are more effective than product-oriented worked examples and whether an expertise-reversal effect occurs when process-oriented worked examples are provided after the learners are familiar with the underlying processes. Methodology. 82 teen aged students with no previous subject matter knowledge volunteered to participate in the study. The students were randomly assigned to one of four treatment groups, including: (a) product-product, (b) process-process, (c) product-process, and (d) process-product training sequences. The study was run in three sessions with participants equally distributed across conditions. The instructional treatment for all of the groups was done through both paper based materials and the TINA Pro software which provided learners with electrical circuit simulations from which either the worked-out solution (product-oriented) or worked-out solution, plus process information (process-oriented) was provided. The process oriented worked examples and product-oriented worked examples contained the same steps, but the process-oriented worked examples contained information about the underlying principles, as well as the systematic problem approach. A prior knowledge questionnaire was conducted first followed by material to familiarize the learners with the TINA system they would be using. Each session included two series of training examples. After learners studied the first series of training examples (either product- or process-oriented examples, based on their assigned condition) they completed test problems which required them to troubleshoot a malfunctioning electrical circuit simulation in the TINA system. The learners were also instructed to write down the faulty components on a pre-printed answer sheet and asked to select the reason for the fault from multiple-choice answers. In addition, the learners were asked to gauge their mental effort in studying and solving the problem giving the researchers a measure of mental effort, as well as the noted performance measures. The learners then studied a second series of examples (either product- or process-oriented examples, based on their assigned condition) followed by the test problems and mental effort rating. The study also evaluated the time on task during the tutorial. Results and conclusions. The results supported the researchers’ hypothesis that processoriented worked examples foster early learning and better efficiency as indicated by the learning and mental effort measures. In addition, in line with predictions, the process information Page | 2 Submitted 20081030 IDT 873 Abstracts: Problem Solving Jennifer Maddrell appeared to become redundant as indicated by lower performance measures on the second series which incorporated process-oriented worked examples. Heuristics The results of these experiments suggest that problem solving support for novices should begin with process-oriented worked examples which fully explain the rationale behind the solution and progress to product-oriented worked examples. As suggested by this and other cited studies, process-oriented worked examples can support learning up and until the process information is familiar to the learners at which point it becomes redundant and impedes learning. Critique The findings of this study provide support for prior research on cognitive load and the expertise-reversal effect. As noted, while process-oriented worked examples may initially support the novice learner, they may impede learning in more advanced learners or as the learner progresses. While this study provides support for sequencing of process- and product-oriented worked problems in simple problem solving exercises, the impact on complex problem solving is less clear. As acknowledged by the researchers, further research is needed to assess worked examples sequencing on more complex cognitive skills. Page | 3 Submitted 20081030

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IDT 873 Abstracts: Feedback Jennifer Maddrell Olina, Z., & Sullivan, H. (2004). Student self-evaluation, teacher evaluation, and learner performance. Educational Technology Research and Development, 52(3), Research Purpose and focus. Olina and Sullivan (2004) examined the effect of student selfevaluation and teacher feedback on learning. Their research focused on the comparative and combined performance effects of self- and teacher-evaluation, as well as the effect of both on student and teacher attitudes. Olina and Sullivan predicted that teacher evaluation would improve student performance to a greater extent that self-evaluation. Further, they predicted that selfevaluation would result in better performance and engagement than no-evaluation. Methodology. 341 high school students in Latvia took part in the study. Learners came from 16 classes which were selected from eight schools in different Latvian regions, including a diverse mix of rural and urban areas and of socio-economic backgrounds. Each of the eight schools were stratified based on ability (based on ninth grade standardized Latvian exams) and grouped into either the four higher or four lower ability schools. Each of the four schools in each group were then randomly assigned to one of four treatment groups, including (a) no evaluation, (b) self-evaluation, (c) teacher-evaluation, and (d) self-plus-teacher evaluation groups.. Eight teachers taught two classes each. Over the course of a six week term consisting of two 40 minute class periods per week, all students took the same 12 lesson instructional program about experimental research design which included both a student book and teacher guide. Students in all classes conducted the same experiments, produced written reports as required by the instruction, and were introduced to the project rating scale, a descriptive rubric for evaluating the written projects. However, students in the self-evaluation group formally selfevaluated their own work based on the project rating scale. Students in the teacher-evaluation group were provided written feedback from their teachers based on the same project rating scale. Students in the self-plus-teacher group formally self-evaluated their own work and received written teacher feedback. Students in the no-evaluation (control) group received no formal feedback from the teacher and they were not asked to formally evaluate their own work. Performance measures included ratings of the students’ final projects and posttest scores. In addition, student and teacher attitudes were measured in surveys after the course. Results and conclusions. While there were no significant differences between treatment groups on the posttest scores, the teacher-evaluation and self-plus-teacher groups had significantly higher project scores than the no evaluation group and the self-evaluation groups. Further, in both self-evaluation groups, over 90% of students rated their projects higher than the experimenter-based rating in the final projects. Students in both groups with formal selfevaluation reported more positive attitudes toward the program as compared to the other groups, but both students and teachers preferred teacher-evaluation and felt it provided a more valuable evaluation. Heuristics The results of these experiments suggest that incorporating formal self-evaluation may increase a learner’s confidence in his or her future performance. However, teacher-evaluation alone or combined with self-evaluation is more likely to improve learner performance over no evaluation or self-evaluation alone. Page | 1 Submitted 20081104 IDT 873 Abstracts: Feedback Jennifer Maddrell Critique This study, conducted over a six week term, provides support for prior research that suggests teacher feedback improves student performance. While no significant differences were found in posttest measures, the results suggest that teacher feedback may provide superior learning outcomes (based on other than test application measures) as compared to no evaluation feedback or self-evaluation feedback. Yet, the results do indicate value in learner self-evaluation in terms of increased learner self-control and self-confidence. Page | 2 Submitted 20081104