IDT873 CTA Maddrell - Upload a Document to Scribd

Cognitive Task Analysis Running head: COGNITIVE TASK ANALYSIS 1 Cognitive Task Analysis Jennifer Maddrell Old Dominion University IDT 873 Advanced Instructional Design Techniques Dr. Gary Morrison October 15, 2008 Cognitive Task Analysis Traditional Task Analysis A traditional procedural task analysis describes a task as a series of discrete actions (Jonassen, Tessmer, & Hannum, 1999). Figure 1 diagrams a procedural task analysis for the insurance underwriting submission review task. Within this triage task, the underwriter must evaluate various aspects of the new submission and decide whether to quote or decline the submission. Figure 1. Procedural Analysis of Insurance Underwriting Submission Review Task. 2 Guide to symbols: = Input and exit point; = Mental operation; = Decision Point; = Direction in Step Cognitive Task Analysis 3 As depicted in Figure 1, in completing the submission review task, the underwriter must make a series of mental operations and decisions in route to a conclusion to either a) decline the submission or b) quote the submission. These mental operations and subsequent decisions include the following: Assessing the viability of the opportunity. Upon receipt of the submission, the underwriter must make a quick review of the information provided to assess the viability of the opportunity. Given the information presented within the submission and discussions with the broker, the underwriter must judge the likelihood the account will actually leave the incumbent carrier. Critical cues to consider include prior service and claims handling problems with the incumbent carrier, time to transition the account, and completeness of the submission. If the relationship with the prior carrier has been good, there is little time to transition the account, or the broker only provided enough information to provide a price (not service) quote, it is likely the insured is not serious about moving from the incumbent carrier and the broker is just seeking comparative price quotes. However, if the insured is dissatisfied with the incumbent carrier’s service, there is ample time to transition the servicing of the account, or the submission provides a comprehensive overview of both price and service requirements, it is likely the opportunity is viable. If the assessment of the information leads to a conclusion that the chances are slim the account will move, the underwriter makes the decision to decline the account. However, if the assessments leads to a conclusion that there is a good chance of writing the account, the underwriter makes the decision to continue working on the account. Examining the employee concentrations. Given the potentially catastrophic exposure of providing casualty insurance at locations with high employee concentrations, the underwriter’s triage of the submission includes an examination of employee concentrations. If the insured has employee concentrations at any one location above company guidelines, the underwriter makes the decision to decline the account. Otherwise, the underwriter makes the decision to continue working on the account. Comparing the account’s exposures to the company’s underwriting guidelines. Upon receipt of the submission, the underwriter must compare the prospective account’s exposures to the insurance company’s underwriting guidelines. Critical to this comparison is a review of the insured’s current and prior operations. If the company is involved in any operations which result in exposures that are against the underwriting guidelines, the underwriter makes the decision to decline the account. Otherwise, the underwriter makes the decision to move forward with the quotation task (beyond the scope of this submission triage task analysis). Cognitive Task Analysis A cognitive task analysis (CTA) offers an alternative means of describing the cognitive elements of the evaluation and decision making processes involved in the task. The following provides the results of an Applied Cognitive Task Analysis (ACTA) based on interviews conducted with an underwriting subject matter expert (SME) to gain information about cognitive strategies used to complete the submission triage task (Militello & Hutton, 1998). The ACTA includes a task diagram, knowledge audit table, simulation interview, and cognitive demands table. Cognitive Task Analysis 4 Task diagram Figure 2 is the task diagram generated after an initial interview with the underwriting SME. The task diagram offers a high level overview of the submission triage task which focuses on the most difficult cognitive aspects. The SME was asked, “Think about what you do when you triage a new prospect. Can you break this task down into less than six, but more than three steps?” The SME mentioned five steps, but one was eliminated (financial approval) as it is not task performed by underwriter. Figure 2. Task Diagram for New Account Prospect Triage. Knowledge Audit Table During interviews with the SME, the interviewer probed for concrete examples, cues and strategies, and reasons why the task is often difficult for novices. The interviewer asked the SME to focus on specific examples for each aspect of expertise. Table 1 summarizes the results of the knowledge audit for the submission triage task. Simulation Interview During a simulation interview with the SME, the interviewer asked the SME to focus on the challenging aspects of a specific representative scenario associated with new submission triage. Table 2 summarizes the results of the simulation interview, including the actions, assessments, cues, and potential errors identified for each central event. Cognitive Demands Table Table 3 consolidates and synthesizes the data collected during the interview process. The cognitive demands table centers on the common themes that came from the interviews and identifies the difficult cognitive elements, common errors, and cues or strategies used by experts to overcome these challenges. Cognitive Task Analysis Table 1. Knowledge Audit Table. Aspect of expertise Past and future Example: Call from broker about account where incumbent carrier messed up on claim and insured’s legal department insisting the account must move. 5 • • Cues and strategies High level nature of incumbent mess up Level of people involved in decision (low level versus high level) • • Why Difficult? Novice may not recognize significance of messed up claim handling Novice may not link level of insured to severity of problem Novice may not link severity of problem to increased chance of writing account. Novices may not consider other issues beyond price that influence buying decision Novices do not have relationship with broker to know when you are getting the “straight” facts versus a “sales pitch” Novices may get into the minutia of the account specifics and not step back and realize the timeframe is not feasible to actually move the account Novices are focused on details within submission Novices are familiar with “outside” considerations that affect the likelihood of writing the account • • • • Big picture Example: Steps back from all the facts about the account presented by the broker to consider what is the “real” motivation behind looking for a quote? Is this prospect a true opportunity or does the broker just need a competing price quote? If it is only a need to get competing price quotes, highly unlikely the account will move. Noticing Example: Broker not soliciting TPA quotes for claim handling which would be a #1 condition of actually moving the account. Job Smarts Example: Focus on what broker said in conversation versus purely what is presented in the quote. Opportunities Example: Our unit can’t work on this account, but other units in company can. Anomalies Example: Broker doesn’t return phone calls. Shows a lack of interest. • • • • Beyond price, there service issues with prior carrier Your personal history with that broker. Time frame to release quote What other carriers are quoting • • • • • Going beyond underwriting information presented in the submission Considering conditional things that impact your quote Timeframes Others carriers being asked to quote. Reasons for leaving Understanding of underwriting appetite of other units Knowing how to access those people Timing of returned phone calls Extent of response to questions • • • • • • • • • Novices tend to be preoccupied with verifying details within submission Novices not aware of situational issues that can be “deal breakers” or “deal makers” Novices don’t know underwriting appetite of other units Novices don’t know people outside of the unit Novices may not recognize they are “getting blown off” and they continue working on submission • • Cognitive Task Analysis (either lacking or detailed) 6 • Novices don’t recognize significance of “out of sight / out of mind” which is signal if you are alive or dead Table 2. Simulation Interview. Events Discussion about prospect with broker Actions Ask probing questions about opportunity Sensing tone from broker of urgency and desire to have you quote. Assessment Answers to question make sense or not with what is in the submission Broker wants to work with you or just wants a quote for comparison purposes How much time is there between now and effective date? Are the exposures inherent in risk acceptable under our underwriting guidelines? Critical Cues Can you meet the issued There is disaffection with incumbent Openness of the broker Willingness to provide additional information Too much time signals the broker is “shopping” for an early quote. Too little time signals that broker just wants to keep current carrier “honest” “Red flag” exposures that we cannot write “Go” classes of business that we are targeting Potential Errors Being overly optimistic about any opportunity Not probing deeply for hidden facts about situation Not reading the verbal and nonverbal cues the broker is giving you. • • • • • • • • • • • Deciding whether to quote • • Evaluating time frame between quote deadline and effective date Assessing if account meets underwriting guidelines • • • • • • • • • Being so excited about the opportunity that you rush to judgment Spin wheels on accounts where there isn’t a true opportunity Don’t dig deeply enough into what the account really does or did in the past that could represent “hidden” exposures Cognitive Task Analysis 7 Cognitive Task Analysis 8 Table 3. Cognitive Demands Table. Difficult cognitive elements Assessing whether broker’s answers make sense or not with what is in the submission Considering the “real” opportunity and exposures beyond the obvious information given in the submission Comparing account’s exposure information with underwriting guidelines Why difficult Common errors Cues and strategies used • • Consider if you really know the story behind the story Get and keep the broker talking to elicit information beyond the submission Ask about reasons why account would move Consider whether timeframe to move account is realistic • • • • • • • Considering and suggesting alternatives • • Novice underwriters tend to focus on basic facts in the submission versus what the broker is telling them Brokers reluctant to voluntarily air dirty laundry about account Novices underwriters tend to focus on information given versus information needed to make decision Can be uncomfortable situation for novice underwriters to probe for answers Companies often have many types of operations which cross several classes of business Novice underwriters tend to focus on the primary business operations Novice underwriters often have difficult assigning an account to the appropriate business classification within the guidelines. Novice underwriters tend to focus on what broker is asking you to do Novice underwriters often fail to identify ways to adjust quotation options to meet guidelines • • Don’t recognize or probe for hidden “red flags” Focus exclusively on information in submission Taking the submission at “face value” Failing to engage in uncomfortable probing conversations with the broker Failing to fully capture exposures Getting lost in the details Misinterpreting underwriting data Misinterpreting the underwriting guidelines • • • • • • • • • Review account with senior underwriter Check multiple sources to evaluate exposures • • • Quote only what is asked by broker Failing to probe for alternate opportunities with the broker • • Consider ways to adjust quotation options to fit within underwriting guidelines. Consider other coverages and limits that you or other departments could quote Cognitive Task Analysis Comparison of Approaches 9 Analysis Comparison In comparing the results of the traditional task analysis with the cognitive task analysis, significant differences emerge in following areas: a) the identification and analysis of hidden cognitive processes, b) the relative level of elaboration regarding the central task elements, c) the focus on expert and novice differences. Overt behaviors versus cognitive processes. The key strength of the traditional task analysis is the ability to examine overt behaviors required to complete a task. However, as seen in this example, additional critical cognitive processes and actions were uncovered within the ACTA. Further, the ACTA offered a means of analyzing the relative significance and difficulty of the required task elements. Level of elaboration. The traditional task analysis identified the relevant processes and decision points in the submission triage task. However, by focusing on the difficult cognitive aspects of the task, the ACTA provided greater elaboration with regard to the knowledge and cognitive processes required to perform the task. As the cognitive demands table highlights, the ACTA focused attention on the difficult cognitive elements, common errors, and strategies to overcome those difficulties and errors. Unfortunately, these elements were not unearthed within the traditional task analysis. Focus on expert and novice differences. Unlike the traditional task analysis, the ACTA analysis focused on the central differences between how an expert and a novice perform the submission triage task. The result is a comparison of current state (novices) and desired state (experts), as well as strategies to take the novice to an expert level. Implications for Practice Traditional task analysis allows practitioners to target the inputs, central operations, and decision points involved in carrying out a task. While this provides a good overview of what happens as the task is carried out, it does not provide the designer with an understanding of the nature of the cognitive processes required to complete the task. Further, following a traditional task analysis, the practitioner cannot gage the relative importance of the various tasks elements or which aspect(s) of the task are harder for the novice. As seen in the results between the two analyses, the cognitive task analysis provides practitioners with a better understanding of the difficult and critical cognitive processes, as well as the and cues and strategies, which are central to successful completion of the task. When to use Traditional Task Analysis versus Cognitive Task Analysis Both a traditional task analysis and cognitive task analysis highlight key aspects of the task. However, as seen in the two analyses above, each produces different results. As noted, the cognitive task analysis offers a better analysis of the central knowledge and decision making cognitive processes. Given that each task is different, the following provides a comparison of which analysis is more appropriate based on the degree of observable behaviors, the degree of required expertise, and the relative cognitive difficulty of the task. Cognitive Task Analysis 10 Degree of observable behaviors. The difference in outcomes between the two approaches is likely less significant when the task involves primarily observable behaviors. However, if the task involves primarily mental actions that result in less observable behaviors, a cognitive task analysis is the more appropriate option. Expert versus novice differences. When little task related expertise is required to perform the task, the results of both analyses would likely be similar. However, if successful completion of the task requires knowledge that a novice would not possess, a cognitive task analysis allows the practitioner to uncover or drill down on the difficult cognitive elements. As noted, these cognitive elements are less likely to be adequately analyzed in a traditional task analysis. Relative cognitive difficulty. While a traditional task analysis provides a comprehensive outline of the steps in the task, it does not offer a relative assessment of which steps are harder or more critical to successful completion. Instead, each step in the task is considered equally. However, as seen in the cognitive demands table, some tasks hinge on a smaller number of critical or difficult elements. Therefore, the ACTA is more appropriate when successful task outcomes depend upon cognitively difficult judgments or decision. Cognitive Task Analysis 11 References Jonassen, D. H., Tessmer, M., & Hannum, W. H. (1999). Task analysis methods for instructional design. Mahwah, N.J.: L. Erlbaum Associates. Militello, L. G., & Hutton, R. J. B. (1998). Applied cognitive task analysis (ACTA): a practitioner’s toolkit for understanding cognitive task demands. Ergonomics, 41(11), 1618-1641.

IDT873 Maddrell Concept Abstract 6 - Upload a Document to Scribd

IDT 873 Abstracts: Concepts Jennifer Maddrell 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. Research Purpose and focus. Klausmeier and Feldman (1975) focused their research on concept attainment which they defined within their study as the ability to a) discriminate defining attributes, b) name the concept and each defining attribute, c) evaluate examples and nonexamples, and d) define the word representing the concept. In reviewing prior literature on concept attainment, they highlighted four categories of variables generally studied, including 1) a rational set of examples and nonexamples, 2) definitions of a concept (based on the relevant attributes of the concept), 3) emphasizers to facilitate discrimination, and 4) feedback. The purpose of this study was to evaluate the effect of presenting various combinations of concept definitions and rational sets. They predicted better attainment from those presented with both a rational set and a definition than those presented with either one or the other. Further, they predicted better attainment from those presented with the definition and additional different rational sets. Methodology. 134 fourth-grade students from two Wisconsin (Go Badgers!) elementary schools participated in the study. The students were stratified into high, medium and low levels based on their performance on the most recent Iowa Tests of Basic Skills test. The subject matter concept was the equilateral triangle. Students within each stratification level were randomly assigned to one of four treatment groups which included those presented with 1) a definition of the concept without examples or nonexamples, 2) a rational set of three examples and five nonexamples, 3) a combination of the same definition and rational set, and 4) a combination of the same definition and three different rational sets of three examples and five nonexamples. The treatment lesson was presented in four printed lesson booklets. Following instruction, students were given 1 minute to read each lesson page and then were instructed to turn to the next page allowing 5 minutes per lesson booklet. Immediately following the last lesson, a classification task within a printed booklet measured concept attainment. Without time limit, students viewed 38 instances and were asked to identify whether the instance was an example (by circling yes) or nonexample (by circling no) of an equilateral triangle. Results and conclusions. Means for the stratified groups reflected the initial levels with means for high > medium > low. As predicted, no significant difference in concept attainment was found between those who were presented with either a definition or a rational set. Contrary to the researchers’ prediction, there was also no significant difference from a combination of a definition and the single rational set. However, there was a significant difference between those presented with a definition and those who also received three rational sets. These findings are important as they suggest an advantage for presenting additional rational sets of examples and non-examples. Heuristics The results of these experiments suggest that designers should augment the presentation of the concept definition with multiple rational sets of examples and non-examples when teaching concepts. As seen in this experiment, providing learners with additional rational sets to consider may increase their attainment of the concept. Critique Page | 1 Submitted 20081008 IDT 873 Abstracts: Concepts Jennifer Maddrell The results of this study are important as they provide support for the hypothesis that presenting learners with more examples and non-examples is better. However, if three sets of examples and non-examples are better than one, is more than three even better? A criticism of this study is the short intervention and the focus on a single math related concept. Would these results be replicated over a longer period of time with other types of concepts and with different age groups of learners? 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. Research Purpose and focus. Tennyson and Rothen (1977) sought to expand the previously reviewed work of Klausmeier and Feldman (1975) by evaluating the effect on concept attainment of adapting the number of examples and nonexamples based on individual need. They predicted that an adaptive design strategy that varied the presentation of examples and nonexamples based on student need would improve concept attainment over a nonadaptive strategy. Methodology. 67 undergraduate students participated in the study. The students were randomly assigned to one of three treatment groups, including 1) full adaptive, 2) partial adaptive, and 3) nonadaptive. The adaptive designs were modified using a computer-based Bayesian adaptive strategy which altered the number of examples learners viewed based on a) pretreatment measures of aptitude, b), pretests of prior achievement, and c) task performance. A pretest, treatment lesson, and posttest were administered individually via computer. The untimed lesson focused on two legal concepts, including best evidence rule and hearsay. For all groups, the learning task defined the concept based on the critical attributes of the concepts. The number of instances presented to students varied based on their assigned treatment group. The nonadaptive group received the same number of instances. The number of instances in the partial adaptive model was based on pretest data while the number presented within the full adaptive model was modified based on both pretest data and on-task responses. The study also evaluated the time on task which did not include pre- or post-test time. Results and conclusions. While no significant mean differences were found in pretest measures, significant mean differences were reported regarding time on task and posttest score measures. As predicted by the researchers, the results suggest that full adaptive strategies were more effective than partial adaptive strategies and that the two adaptive strategies were more effective than nonadaptive conditions. In addition, the full adaptive group finished the program significantly faster than the partial group which in turn finished faster than the nonadaptive groups. In attempting to explain the results, the researchers suggest that learning tasks where instance presentation is not modified based adaptive strategies may not keep learners’ interest in the task. Heuristics The results of these experiments suggest modifying instructional concept presentation based on learner mastery. Based on the findings of this study, presentation of examples and nonexamples after the learner has achieved mastery may result in learners losing interest in the learning task. Critique Page | 2 Submitted 20081008 IDT 873 Abstracts: Concepts Jennifer Maddrell The results of this study are important as they suggest that optimal presentation varies based on the each individual learner’s level of mastery. In this controlled experiment, using a computer based model, the researchers were able to alter the individual presentation based on each learner’s level of mastery which resulted in more effective instruction. However, altering presentation to an individual learner in real-world instructional settings is difficult, especially in group face to face settings. Therefore, while the results suggest an important finding with regard to tailoring instruction to meet the individual learner, such modifications may not be feasible in practice. Page | 3 Submitted 20081008

IDT873 Maddrell Cognite Load Abstract 4 - Upload a Document to Scribd

IDT 873 Abstract: Cognitive Task Analysis Jennifer Maddrell van Merrienboer, J. J. G., Kirschner, P. A., & Kester, L. (2003). Taking the Load Off a Learner's Mind: Instructional Design for Complex Learning. Educational Psychologist, 38(1), 513. Overview Citing decades of prior cognitive load theory and research, van Merrienboer, Kirschner, and Kester (2003) offer a theoretical framework and instruction design model for complex learning. Noting a recent emphasis on authentic learning tasks (such as project and problembased learning approaches) to support complex learning, they consider the implications on cognitive load and offer a model designed to manage both intrinsic and extraneous cognitive load. Theory While the theories underlying the use of authentic learning tasks may vary, a common assumption is that authentic tasks help learners to integrate the knowledge and skills necessary for complex task performance (van Merrienboer et al., 2003). However, given the novice learner’s weak problem-solving methods, they face high extraneous cognitive load when confronted with authentic tasks. In addition, the complexity inherent in the authentic task presents high intrinsic cognitive load. Therefore, based on cognitive load theory, engaging in highly complex authentic learning tasks may strain the novice learner’s limited working memory and subject the learner to excessive cognitive load. Proposal van Merrienboer et al. focus their attention on both the nature and the delivery timing of the presented information. They suggest that supportive information (knowledge necessary for problem solving and reasoning) is best presented before the learner engages in the learning task. Such supportive task specific information is inherently complex and needed in order to know how to approach the learning task. Presenting the supportive information first helps learners construct schemas to be used as they begin task performance. In contrast, van Merrienboer et al. suggest that procedural information (the how to instructions for rule application) is best presented when needed during task performance. They argue that such just-in-time presentation of procedural information reduces the potential for splitattention effects that may occur when the learner attempts to integrate procedural information learned previously with actions he or she is taking now. Heuristics From these suggested practices, van Merrienboer et al. offer an instructional design model (the 4C / ID model) for complex learning that focuses on four components: 1) learning tasks, 2) supportive information, 3) procedural information, and 4) part-task practice. The heuristics for designers within the 4C / ID model is to sequence from simple versions of the whole task beginning with a high level of support and ending with a complex version without support. In addition, as discussed above, supportive information is to be presented in advance of performance while procedural information required to perform the task is to be presented as the task is being performed. Finally, to encourage automaticity, additional repetitive practice should be incorporated for parts of the task. Critique The focus of the article is not an examination of the effects of authentic learning tasks on learning, but rather the implications of incorporating such tasks on the learner’s cognitive load. As such, the article offers a bridge across theory, research, and practice. A key strength of the article is the authors’ focus on the reality of limited working memory and the high cognitive load IDT 873 Abstract: Cognitive Task Analysis Jennifer Maddrell imposed by authentic learning tasks. The 4C / ID model offers designers a way of incorporating authentic tasks while at the same time better managing cognitive load. However, as a theoretical article, it does not offer results from a study of the model in practice. Do the heuristics within the 4C / ID model help to manage cognitive load? Further, do authentic learning tasks designed within the framework of the 4C / ID model effectively and efficiently support learning? These questions are left to future research.

IDT873 Maddrell Cognitive TA Abstract 3 - Upload a Document to Scribd

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IDT 873 Abstract: Cognitive Task Analysis Jennifer Maddrell Schaafstal, A., Schraagen, J. M., & van Berlo, M. (2000). Cognitive task analysis and innovation of training: The case of the structured troubleshooting. Human Factors, 42(1), 75–86. Research Overview. Following an instructional design evaluation of an existing Royal Netherlands Navy maintenance training course, Schaafstal, Schraagen, and van Berlo (2000) observed a gap between the instruction and the practice of troubleshooting the subject system. They observed that the existing instruction was based largely on the technical equipment documentation from engineers which focused exclusively on the system’s components. Following a comprehensive cognitive task analysis (CTA), Schaafstal et al. revised the instruction under the assumption that maintenance system troubleshooting is a complex cognitive task requiring not only knowledge about the system’s components, but also knowledge about how the system functions and how to consider possible causes and solutions to maintenance problems. The CTA consisted of several observational studies of troubleshooting with technicians of varying expertise levels. Based on information from the CTA, a modified course was prepared which focused on a functional understanding of the system versus the component orientation of the prior course. In addition, general troubleshooting strategies were incorporated which gave learners instruction on how to a) describe the problem, b) generate causes, c) test causes, d) repair, and e) evaluate solutions. Purpose. The purpose of the presented research was to evaluate the modified structured troubleshooting training course and to compare it with the exiting maintenance training course. Schaafstal et al. predicted superior outcomes from the revised course. Methodology. A series of experimental studies compared the learning outcomes of maintenance trainees taking the new structured troubleshooting training course with groups of maintenance trainees taking the existing training course. Outcome measures included malfunction identification, reasoning, and functional understanding of the system. Conclusions. The modifications in the course reduced the course duration by 33% (from six to four weeks). Even at the shortened length, those participating in the new course achieved statistically superior results as compared to those in the original course. Based on the results of the study, Schaafstal et al. suggest that novice technicians lack both a systematic approach to troubleshooting, as well as a functional understanding of the equipment. As seen in prior research, they observed that novices face information overload (lose the forest for the trees), lack hierarchically organized cognitive frameworks, lack functional understanding, possess inadequate mental models of underlying system, and lack the ability to isolate causes of the problem. Therefore, based on the results of their evaluation, they suggest that training in troubleshooting should focus on three areas: 1) system independent troubleshooting strategies to be used across systems, 2) system specific functional models, and 3) system specific domain knowledge. Heuristics Results of this research suggest the importance of moving away from a purely component oriented analysis to what the researchers term a functional decomposition when designing troubleshooting skills instruction. While analysis and instruction on the components is necessary, it is not sufficient. Analysis and instruction should also focus on the functional processes, including likely causes of potential problems and paths to solutions, in order for learners to know what to do when troubleshooting. Further, the results indicate that training in system independent troubleshooting skills can further augment the troubleshooting skills instruction. IDT 873 Abstract: Cognitive Task Analysis Jennifer Maddrell Critique The presented research is important for two reasons. The research suggests a positive influence of CTA on outcomes in troubleshooting training. By revising the instruction to focus on a functional understanding of the system from information gleaned in the CTA, the instruction appears to have been significantly improved. In addition, the findings suggest a positive impact from teaching system independent troubleshooting skills. Also, the paper is valuable for the information provided about the evolution of the authors’ CTA process. This information will be helpful to future designers and researchers. Unfortunately, the written presentation of this paper is horribly disjointed. It is doubtful that most readers will devote the time necessary to weave a coherent narrative out of the broken threads of theory, prior research, CTA processes, instructional design considerations, research methodologies, and conclusions. There is a wealth of information included in the paper, but unfortunately the reader must devote an unnecessary amount of effort to piece it all together.

IDT873 Maddrell Behavioral Abstract 2 - Upload a Document to Scribd

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Behavioral Strategy Abstract Running head: BEHAVIORAL STRATEGY ABSTRACT 1 Behavioral Strategy Abstract: Self-Pacing Versus Instructor-Pacing Jennifer Maddrell Old Dominion University IDT 873 Advanced Instructional Design Techniques Dr. Morrison September 8, 2008 Behavioral Strategy Abstract Self-Pacing Versus Instructor-Pacing 2 Overview Morris, Surber and Bijou (1978) report on research conducted to compare achievement, student satisfaction, and retention between self-paced and instructor-paced personalized systems of instruction (PSI). While noting that one of the key features of PSIs is the ability for learners to self-pace, the authors cite prior research that suggests students who are allowed to self-pace may be more likely to procrastinate or withdraw from the course entirely. These finding have led some to incorporate instructor-paced schedules into the PSI. However, what had been less clear in prior research is the impact of self-pacing on learner achievement (both short term and longer term following course completion) and learner satisfaction with the learning experience. Research Purpose. The purpose of the reported study is to compare progress rates, withdrawal rates, achievement, satisfaction, and longer term retention between learners completing selfpaced or instructor-paced PSI. The researchers set out to extend prior research by focusing on the effect of pacing on these measures. Methodology. All 149 students enrolled in an introductory child development class were randomly assigned to either self-paced (S-P) or instructor-paced (I-P) PSI. The syllabi, course materials, and assessments were identical for both groups. Within each of the 15 units of the PSI, all learners were required to either achieve 90% mastery within a 10-item short-answer essay quiz and oral examination at a testing center or take a make-up quiz until 90% mastery was achieved. Learners in the S-P condition were able to complete all 15 required units within the PSI at their own pace within the semester. Semester grades for the S-P group were based solely on the number of units mastered. In contrast, the I-P students were subject to a grading scheme that could result in a one letter grade drop if the student did not complete at least one unit of material each week. To evaluate and compare pacing, the semester was divided into five 15 day increments. For the purpose of measuring student achievement, a 53 item multiple-choice pre and post-test based on a few items from each unit was administered to all learners. In addition, nine months after the semester, students were asked to return (with compensation) for a follow-up test. They were all informed that the pre and post-tests would not impact final grades. A course evaluation questionnaire addressed student satisfaction with the course. Conclusions. As shown in prior research, the completion rates between the S-P and I-P groups were not the same. I-P learners progressed through the material at a more even rate throughout the semester, while S-P learners completed fewer units in the initial time periods as compared to the latter time periods. However, there were no statistically significant differences in course withdrawal rates, final grade distributions, course evaluations, or achievement measures between the two groups. Yet, there were statistically significant differences between the number of repeated quizzes during the semester and the follow up retention scores. S-P students repeated 4.1% of their quizzes, while I-P students repeated 7.2% of theirs. While the S-P learners’ delayed rate of completion may signal cramming or procrastination, self-pacing did not appear to negatively impact course achievement or Behavioral Strategy Abstract 3 withdrawal rates which were two areas of concern in prior PSI practice and research. Further, the S-P learners’ ability to control pacing may have aided in their longer term retention of the material. Heuristics Based on the results of this experiment, lesson pacing by the instructor or designer may reduce cramming and procrastination, but may do nothing to improve learner achievement, overall satisfaction, or course retention. Further, allowing learners to self-pace may improve their longer term retention of the material. However, it is important to note that these results are based on otherwise rigid instructional parameters in which learners were required to complete highly structured lesson units during the single semester. Therefore, while the learners were allowed the ability to complete the units at their own pace during the course of the semester, they otherwise had little control. As such, it is unclear if this heuristic would apply to a more flexible learning environment in which the learners had more choice, such as in the selection or sequencing of instructional content. Critique of Article A key strength of this research is the direct comparison of pacing on achievement, retention, satisfaction, and longer term retention within an otherwise highly structured instructional setting. The research methodology appears effective at comparing the two types of PSI pacing schemes. However, as noted above, these results are based on otherwise rigid instructional parameters. It is unclear if these results would be replicated in situations where more learner choice and control is available. In addition, the research has done little to further an evaluation of the effect of PSIs on a broad range of learning outcomes. In reporting on learning achievement, the authors do not elaborate on what was learned. Did the PSI lead to anything more than basic recall and retention of facts or concepts? Are the learners able to apply the instruction in diverse contexts? Unfortunately, the authors offer the results as a demonstration of learning achievement, but it is unclear from the results what precisely was learned. Behavioral Strategy Abstract References Morris, E. K., Surber, C. F., & Bijou, S. W. (1978). Self- versus instructor-pacing: Achievement, evaluations, and retention. Journal of Educational Psychology, 70(2), 224-230. 4

IDT873 Maddrell Generative Abstract 1 - Upload a Document to Scribd

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Generative Strategy Abstract Running head: GENERATIVE STRATEGY ABSTRACT 1 Note Taking as a Generative Strategy Abstract Jennifer Maddrell Old Dominion University IDT 873 Advanced Instructional Design Techniques Dr. Morrison September 2, 2008 Generative Strategy Abstract Note Taking as a Generative Strategy 2 Overview Citing a large and conflicting body of prior research, Peper and Mayer (1986) suggest that three main hypotheses are forwarded by prior research on the effect of note taking on a learner’s cognitive processing, including 1) the attention hypothesis (note takers pay closer attention to the to-be-learned material), 2) the distraction hypothesis (note takers concentrate on the act of writing instead of listening), and 3) the generative hypothesis (note taking enables learners to actively relate material to existing knowledge). Peper and Mayer suggest that evaluations of both attention and distraction hypothesis have tended to focus on how much is recalled. In contrast, by focusing on the generative hypothesis within their reported experiments, the goal is to evaluate the difference in what is learned between note takers and non-note takers. Research Focus. Perry and Mayer (1986) focus on three generative hypothesis predictions. The first prediction is that note takers will perform better on far-transfer test measures (problemsolving) and worse on near-transfer test measures (verbatim recognition and fact recall). This is based on the assumption that note taking offers an opportunity for integration with existing knowledge, but the process of reorganizing the new information interferes with near-transfer verbatim recall of specific facts. Secondly, these results will be stronger for those unfamiliar with the material given the processing required to integrate and organize new information. Finally, the results associated with the note taking generative activity will be similar to those for other types of generative activities. Methodology. Two separate experiments were conducted to test these predictions. The first experiment involved a group of high school students while the second included college students at the University of California at Santa Barbara. To test the first hypothesis, Experiment 1 included only subjects unfamiliar with the to-be-learned topic. The students were divided equally between either a “notes” and “no-notes” group. The same video lecture was shown to each group. Afterward, the notes were collected from the “notes” group and the same posttest was administered to both groups. Recognition questions asking the students to identify sentences that occurred verbatim in the lecture were followed by fact retention and problem solving questions. To assess the second and third hypothesis, Experiment 2 included some subjects who were familiar with the topic and added a question-answering treatment group. The same materials and posttests were used for both experiments. Conclusions. In contrast to the attention hypothesis, the superior results of the “no-note” group to verbatim recognition measures does not support the prediction that note taking results in better total recall. Further, in contrast to the distraction hypothesis, the “notes” group performed better than the “no-note” group in some measures. However, significant differences existed between the measures of what was learned (far-transfer versus near-transfer measures) supporting the generative hypothesis. Note takers excelled on the far-transfer (problem solving) test measures. In contrast, “no-note” takers were more successful in near transfer verbatim and fact recall of information. Supporting the second prediction, the results in Experiment 2 were strong for learners unfamiliar with the topic, but not for familiar learners. Further, in support of Generative Strategy Abstract 3 the third prediction, the other tested generative activity (within the questioning-answering treatment) had similar results as note taking. Perry and Mayer (1986) viewed these results as support for generative theory. They concluded that the process of note taking (especially for those unfamiliar with the material) encourages the note takers to assimilate new information with past experience and make interconnections among pieces of information. Heuristics Based on the results of these experiments, learners should be offered the opportunity to take notes as a means of supporting the long term encoding of new information. This research suggests that the note taking process offers learners the opportunity for integration and organization of the new information with existing knowledge. However, this research also suggests that these results are more likely when the to-be-learned information is unfamiliar to the learner. Further, the process of re-organization and integration with prior knowledge involved in note taking may interfere with verbatim encoding of information and facts. Critique of Article A key strength of this research is the evaluation of note taking across three separate hypotheses, including attention, distraction, and generative theories. Further, the research highlights the advantages, as well as potential limitations, of note taking on encoding. However, it is important to note that the test measures were based on cued recall versus free recall. A possible source of future research would be to replicate the experiments with free recall test measures. In addition, the research analysis did not provide a qualitative analysis of the notes taken by students. An analysis of the qualitative features of the notes, such as the use of diagrams, would have helped to augment the findings. Also, as noted by the authors, this research provides an incomplete analysis of the relationship between note content and problemsolving performance. Generative Strategy Abstract References 4 Peper, R. J., & Mayer, R. E. (1986). Generative Effects of Note-Taking during Science Lectures. Journal of Educational Psychology, 78(1), 34.

Policy Issues in Distance Education - Upload a Document to Scribd

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Policy Issues 1 Running head: POLICY ISSUES IN DISTANCE EDUCATION Policy Issues in Distance Education Jennifer Maddrell Old Dominion University Policy Issues 2 Policy Issues in Distance Education Institutions providing distance education face unique policy issues which impact students, instructors, and the institution. This report assesses six issues that are of particular importance to distance educators, including 1) student copyright and privacy protections, 2) tuition and fee structures, 3) library resources and services, 4) copyright and ownership of course material, 5) instructor compensation and support, and 6) Internet access and connection support. This assessment highlights examples of how various institutions address these issues within their formal policy statements and provides an analysis of each policy issue. Issue 1: Students Copyright and Privacy Protections Policy Issue and Examples There are numerous reasons why an instructor would want to share a student’s work with other current or future students or to capture and share a recording of students engaged in a course sessions. The recorded sessions can be replayed for future classes and a student’s work can offer an exemplary example to other students. However, there are important copyright, confidentiality, and privacy implications associated with using a student’s work or image in either distance or on-campus instruction. The following highlights examples of policies established by the University of Michigan, the University of California system, Buffalo State College, and Western Governors University to address these issues. Student’s Copyright Protections: Within its copyright policy, the University of Michigan outlines the copyright protections afforded to students and clarifies that a student holds the copyright to the academic works he or she creates, including papers, projects, theses, and dissertations. Similarly, the University of California Policy on Copyright states that the copyright to a student’s works resides with the student and clarifies that a “student’s work” is Policy Issues 3 considered to be work produced a) by a registered student, b) outside of University employment, and c) without the use of University funds other than Student Financial Aid. Student’s Confidentiality and Privacy Protections: Beyond copyright, there are also confidentiality and privacy concerns related to the release of a student’s work, the recording and replay of his or her image within either a face-to-face or virtual classroom, or the release of any identifying information about the student. Buffalo State College, part of the State University of New York (SUNY) system, clarifies in its policy that “all course-related materials, including but not limited to computer files, data, disks, electronic mail, and local area network communication, for distance education classes should be as confidential as the medium allows consistent with appropriate student access and SUNY and state policy.” Similarly, Western Governors University (WGU) includes in both its policy and agreements with instructors, that the privacy of WGU students to be maintained. Policy Analysis The policies described are designed to ensure compliance with protections afforded students within applicable state and federal copyright and privacy laws, including those found within the Family Educational Rights and Privacy Act (FERPA) which restricts disclosure of non-directory student record information. It is understandable why an institution would chose to clarify and restate these provisions as copyright and privacy laws are not well known by the general public and the interpretation of specific legal provisions can be confusing. Further, adherence to copyright, privacy, and confidentiality laws can be more difficult within an online learning environment where dissemination of electronic material is easy and rapid, yet where it is difficult for students to engage with other students without sharing some degree of personal information, such as e-mail addresses. Therefore, it is recommended that the institution’s Policy Issues 4 copyright and privacy policies address activities specific to the delivery of distance education, such as creation and publication of student work on the Internet, and mandate that the student’s permission must be obtained prior to any release or distribution of his or her work or image. In addition, it is important to clarify within copyright policy when a student could be considered an employee as the copyright protections and provisions granted to employees may be different (see below) depending upon the student’s capacity. Issue 2: Tuition and Fees Structures Policy Issue and Examples In most public institutions and in many private institutions, tuition schedules for oncampus programs are based on the student’s residency status. In general, students without residency status within a traditional on-campus program pay higher tuition rates than students with residency status. However, tuition schemes become more complex when distance delivery modes are introduced. A review of tuition policies at five major university systems reveals a range of tuition and fee structures. Tuition Based on Delivery Mode and Residency Status: Within Penn State University’s World Campus, tuition rates in the fully online programs are the same regardless of the student’s residency status. However, within any other Penn State campus, students pay different rates based on residency states. For example, at current rates, a graduate student with Pennsylvania residency status taking a three credit Instructional Technology course on Penn State’s University Park campus pays $1,815 in tuition and fees, plus an additional campus activity fee, which is identical to the tuition and fees a graduate student in a three credit Instructional Technology course within the World Campus pays, less the activity fee, regardless of residency status. In contrast, a non-resident student attending the University Park campus Policy Issues 5 pays $3,237, 76% more than if the course was taken by a resident of Pennsylvania or if the same student took the course online in the World Campus. The State University of New York (SUNY) tuition policies are similar. Using SUNY’s Empire State College campus as an example, New York residents pay $181 per credit which is the same rate paid by all students in a distance learning course, regardless of residency status. However, like the Penn State model, non-residents pay $442 per credit, 144% more than New York residents, for an on-campus course. Unlike Penn State students, SUNY distance learning students also pay the same College Fee of $0.85 per credit and the Student Activity Fee of $6.25 per credit as the on-campus students in addition to a Telecommunications Support and Development fee of $75 per term. Tuition Based on Residency Status: Ball State University students who are Ohio residents pay $226 per credit for undergraduate courses and $246 per credit for graduate level courses for all online, on-campus, and web conferencing classes. Unlike within either the Penn State or SUNY tuition structure, Ball State University non-resident students pay 70% more in tuition and fees than Ohio residents, even within distance education delivery formats. An identical tuition and fee structure based on residency status, but not delivery mode, is in place within the University of Nebraska system. Tuition Based on Delivery Mode, Residency Status and Location: Public universities in Texas have a complex tuition and fee matrix based on not only the student’s residency status or the delivery mode, but also on where the student is living at the time the course is delivered. Across the board, Texas residents pay the same residential tuition regardless of delivery mode or where they are living at the time they are taking the course. In contrast, non-residents pay non-resident tuition in on-campus or electronic courses, if the student is living in Texas. The Policy Issues 6 non-resident student taking an electronic course while living out of state pays a different tuition rate that is termed “equivalent to Texas resident tuition and fees”, but that is adjusted to cover cost of instruction which results in a tuition rate that is almost identical to tuition assessed to non-residents, living in Texas, and taking classes on-campus. In a 1999 memorandum, Don Brown, Commissioner of the Texas Higher Education Board, outlined this complex tuition policy and the rationale for charging a higher fee to non-Texas residents living outside of the state. Brown noted that if non-Texas residents living outside of Texas pay the same rate as Texas residents, “Texas taxpayers would be subsidizing the education of non-Texans who, unlike non-residents on-campus are not living in Texas, not paying sales and other taxes and supporting the TX economy.” Policy Analysis As noted, there is no standard tuition and fee structure policy across higher education institutions. In general, a school makes tuition allocation decisions based on three variables: 1) the delivery mode of instruction, either on-campus or via distance learning, 2) the residency status of the student, and 3) where the learner resides at the time of the course. While some schools, such as Penn State and SUNY, maintain a relatively simple tuition and fee structure based on one or two factors, such as the delivery mode or the residency status, other schools incorporate additional variables which result in a far more complex tuition and fee structure. In the end, a school must collect sufficient revenue to cover expense costs and achieve profitability targets. As shown, there are various means to adjust tuition schedules to allocate costs among various student types. While the Texas system is devised to contemplate tax payer status and address subsidy equity, market conditions also play a role. As noted within a 2003 University of Nebraska distance education tuition policy memo, campus are “free to charge Policy Issues 7 non-resident tuition at any price the market will bear and will retain as a campus resource the difference between the resident tuition and what is collected.” Therefore, regardless of how and why the allocation structure is established, the tuition policy must ensure that the revenue collected through tuition and fees covers the costs of providing educational services and achieves the institution’s profitability goals. Issue 3: Library Resources and Services Policy Issue and Examples Obtaining library resources and services are a significant obstacle for distance education students. Some institutions, such as Penn State’s World Campus, offer comprehensive library access policies with a vast array of library services for distance education students. Any student enrolled in a World Campus course may borrow resources from the library, including books owned by any Penn State campus location, articles from journals owned by Penn State, as well as books and journals not owned by Penn State and retrieved through inter-loan library agreements. Books owned by Penn State may be kept for a semester loan with two renewals. Books not owned by Penn State may be kept for four to eight weeks. Hardcopy materials are sent by US Mail to the student’s address on file. Students are only responsible for the cost of the return postage, but they can return the book to any Penn State campus library. However, all books are subject to recall and reference, rare books, microfilm, or special collections will not be delivered to students. Indiana University (IU) offers distance students similar library resources and services. However, only books owned by the IU library system will be mailed to students. The loan period is 120 days for graduate students and 45 days for undergraduate students. Books may be renewed only if another person has not requested the book. Hard copy materials are mailed at Policy Issues 8 no charge to the student via US Mail with an estimated ten day delivery period. As with the Penn State policy, the student is responsible for the return mailing fees. Policy Analysis In general, the reviewed policies tend to track with the policy guidelines for distance learning library services approved by the Board of Directors within the Association of College & Research Libraries (ACRL) which holds as its guiding principle that, “Library resources and services in institutions of higher education must meet the needs of all their faculty, students and academic support personnel, regardless of where they are located.” The ACRL guidelines acknowledge that services may differ from the campus library, but that the focus should be on equivalency. To overcome the distance obstacle, they stress establishment of a) “virtual” access to library personnel for reference assistance, consultation, and access to non-print media, b) linkage to electronic resources, and c) the creation of agreements with unaffiliated university and local libraries to provide learners with resources. These guidelines seem reasonable and attainable for most university systems and track with the library privileges granted to distance learners at the reviewed institutions which provide access to vast databases of electronic resources, grant access to campus based librarians, and mail their hard copy resources to distance learners. Issue 4: Copyright and Ownership of Course Material Policy Issue and Examples Policies relating to the copyright and ownership of course material impact the future reuse of course material by the university, as well as the re-use by the instructor as creator of the material. A review of the copyright and intellectual property policies of several institutions reveals a common perspective, namely that copyright and ownership of faculty work created as Policy Issues 9 a specific requirement of employment should reside with the university, unless otherwise stated in the policy or addressed in contractual agreements between the faculty and the university. This perspective is held within the University of California Policy on Copyright Ownership which states, “Except as noted elsewhere, the University shall own all copyrights to works made by University employees in the course and scope of their employment and shall own all copyrights to works made with the use of University resources.” Similarly, Fayetteville State University’s policy maintains that the University owns the materials and retains the right of use, but notes that the instructor and the university may enter into a written agreement to “protect the interest of both parties." Buffalo State College adopted a detailed policy to address copyright and ownership based on the type and scope of work created by faculty highlighting the distinction between works created expressly at the direction of the University and other types of academic work. The policy clarifies that the University is the sole owner of intellectual property when the University, “expressly directs a faculty member or professional employee to create a specified work, or the work is created as a specific requirement of employment, such as might be included in a written job description.” Further, the college and the faculty member are “joint owners of intellectual property when the college has contributed support beyond what is traditionally provided”. However, for all other academic work, the policy states that “intellectual property created by a faculty member … will remain the property of the faculty member … for perpetuity or so long as the law allows. As such, permission is required from the faculty member to use, revise, record, rebroadcast or redistribute such materials.” In contrast, San Diego State University’s policy does not explicitly address copyright and ownership, but defers to the contractual agreement between the University and the faculty Policy Issues 10 member, stating that, "Ownership of materials, faculty compensation, copyright issues, and the utilization of revenue derived from the creation and production of software, telecourses, or other media products shall be agreed upon by the faculty and the University (in accordance with the Intellectual Property Policy) prior to the initial offering of the course or program.” Policy Analysis Springer (2005) provides an overview of the tangle of copyright, ownership, and other contractual issues involved with the production of academic materials. Springer notes that while copyright law itself is straightforward, with copyright belonging to the author at creation, it can be transferred contractually. However, she argues that copyright cannot be unilaterally imposed within institutional policy. In addition, Springer describes how the scope of employment and the nature of the academic work can impact copyright. If the work is deemed “work-for-hire”, the institution (as employer) may be considered the author. While academic work produced by faculty has traditionally not been considered to fall within the scope of “work-for-hire”, distance learning projects, which may be interpreted as outside the ordinary scope of traditional academic work performed by faculty, complicate matters. This is especially true for distance learning projects completed by part time or adjunct faculty. Therefore, it is not sufficient to clarify positions regarding copyright, ownership, and reuse of materials within institutional policy statements. Provisions must be contained within contractual agreements with faculty prior to employment. Further, it is necessary to qualify the scope of the academic work, especially for distance learning projects which may be considered “work-for-hire”. Policy Issues 11 Issue 5: Instructor Compensation and Support Policy Issue and Examples Development of new online courses raises many policy challenges relating to faculty selection, compensation, and support. What faculty should be involved in the development and delivery of the courses? What is the appropriate compensation? What support should be provided? Instructor Compensation: To address rapidly increasing distance education enrollments at the University of Nevada Las Vegas (UNLV), a special distance educational instructional salary and incentives policy was adopted in 2004. As part of the program, faculty members are provided $1,500 per course as “incentive” pay to develop new distance education course offerings. Further, part-time instructor (PTI) per credit salary is paid for teaching a distance education course and is paid to either a part time instructor or a full time faculty member teaching “off-load”. In addition, a faculty member teaching “on-load” receives incentive pay the first time a course is offered. In contrast, at the College of Southern Nevada, either full or part-time faculty receives “one-time compensation” for the development of a distance education course approximating the pay rate of an adjunct instructor. That person does not have to teach the course to receive course development compensation. Instructor Support: Southeastern Louisiana University’s distance education policy affords faculty development support through the Center for Faculty Excellence. Faculty members engaged in distance learning are to receive “priority consideration” in new technology purchases and updates and in technical support in the design and maintenance of the courseware. Similarly, Buffalo State College provides instructors with needed instructional technologies for distance education classes. Further, its policy provides faculty with clerical, Policy Issues 12 technical, instructional design, computing, multimedia, and library support services, as well as opportunities to learn how to use instructional technologies. Policy Analysis The American Association of University Professors (AAUP) has established sample distance education policy and contract language addressing the workload responsibilities and support needs of distance education faculty. The AAUP policy guidelines provide a good outline of important policy considerations relating to instructor compensation and support. Regarding compensation, the AAUP argues that faculty should expect to be compensated a) financially, b) in time to prepare, or c) in the form of credit toward load assignment for the “extra time” required to prepare a distance education course. In addition, courses taught via distance education should be either part of the faculty member’s regular load or as an overload. In terms of support, the AACP maintains that faculty should receive adequate preparation and training, technical equipment and assistance, as well as any needed clerical and library support. Issue 6: Internet Access and Connection Support Policy Issue and Examples Within an online course, it is essential that the learners have Internet access and the necessary hardware and software to connect to the course materials. However, clarification of who is responsible for ensuring access for that connection is an important policy consideration. Buffalo State College’s Internet access policy states that students enrolled in a distance education course while residing on campus will be provided Internet access through campus Internet. However, all other students must secure their own access. Harvard University maintains a similar stance regarding Internet access and includes within its policy that the student must secure the necessary hardware and software, including any course specific Policy Issues 13 software needed to complete course assignments. While San Diego State University’s policy clarifies that it is a student’s right to know the modes of delivery and technological requirements of each course, it is the student’s responsibility to have access prior to course enrollment. Further, prior to registration, students are required to have specific basic technology skills and access to a personal computer. Ball State University assumes added responsibility for providing connection support by offering registered distance students an array of software products for free via download on the University’s website, including Symantec Antivirus, iConnect, iLocker, iWeb, Web Mail, Microsoft Office, and Microsoft Windows. Policy Analysis As noted, Internet access and connection support is critical to the delivery of web based distance education. The American Distance Education Consortium (ADEC), a non-profit distance education consortium of approximately 65 state universities and land-grant colleges, has four guiding principles. The third guiding principles relates specifically to technological infrastructure and support and recommends that distance education institutions provide orientation to the process of learning at a distance, including the use of technologies for learning, and technology, as well as human support for learners and learning facilitators in their use of the technologies. However, nowhere within this guideline is a provision for distance educators to provide access. As within San Diego State University’s policy, a reasonable policy approach is to confirm both the institution’s responsibility to inform students about the modes of delivery and technological requirements of each course, as well as the student’s responsibility to have access prior to course enrollment. Policy Issues 14 References American Distance Education Consortium (ADEC) Guiding Principles for Distance Learning. Retrieved from http://www.adec.edu/admin/papers/distance-learning_principles.html. Association of College & Research Libraries (ACRL) - Guidelines for Distance Learning Library Services. Retrieved from http://www.ala.org/ala/acrl/acrlstandards/ guidelinesdistancelearning.cfm. American Association of University Professors (AAUP): Sample Distance Education Policy & Contract Language. Retrieved from http://www.aaup.org/AAUP/issues/DE/ sampleDE.htm. Ball State University - Software Available to Students. Retrieved from http://www.bsu.edu/distance/article/0,,7521--,00.html. Ball State University - Tuition, Distance Education Program. Retrieved from http://www.bsu.edu/distance/tuition/. Brown, D. (1999, December 20). State Funding and Tuition Policies for Distance Education and Off-Campus Courses - Texas Higher Education Coordinating Board. . Retrieved from http://www.thecb.state.tx.us/reports/pdf/0197.pdf. Copyright at the University of Michigan: Using copyrighted material. Retrieved from http://www.copyright.umich.edu/using_copyrighted_material.html#a8. Distance Education Policies: Harvard University. Retrieved from http://www.summer.harvard.edu/2008/DistanceEd/policy.jsp;jsessionid=PIDJ... MG. Empire State College - State University of New York Undergraduate Tuition and Fees. Retrieved from http://www.esc.edu/esconline/online2.nsf/html/basictuitionandfees.html Policy Issues 15 Fayetteville State University. Fayetteville State University - Continuing/Distance Education Policy. Retrieved from http://www.uncfsu.edu/conted/Distance_Learning_ Policy_2.htm. Family Educational Rights and Privacy Act (FERPA). Retrieved from http://www.ed.gov/policy/gen/guid/fpco/ferpa/index.html. Indiana University Distance Education Document and Book Delivery. Retrieved from http://www.libraries.iub.edu/index.php?pageId=5705. Office of Extended Education & Outreach. (2003, September 9). University of Nebraska Distance Education Tuition Policy. Retrieved from http://extended.unl.edu/faculty/policies/distance_education_tuition.pdf. Office of the President. (1992, August 19). University of California Policy on Copyright Ownership. . Retrieved from http://www.ucop.edu/ucophome/coordrev/policy/8-1992att.html. Office of the Executive Vice President and Provost University of Nevada Las Vegas. (2004, November 17). UNLV Distance Education Instructional Salary and Incentives Policy. . Retrieved from http://provost.unlv.edu/files/DIST_ED_INST_SAL_12.2.04.doc. Penn State Libraries - Library Distance Learning Delivery - Policies. Retrieved from http://www.libraries.psu.edu/tas/ill/policies.htm. Penn State Tuition Calculator. Retrieved from http://collegecostestimate.ais.psu.edu/isapi/CollegeCostEstimate.dll/submit. Penn State | Tuition Calculator for Online Degrees, Online Courses, and Online Certificates. Retrieved from http://www.worldcampus.psu.edu/TuitionTable.shtml. Policy Issues 16 San Diego State University Center for Distance Learning. Retrieved from http://interwork.sdsu.edu/cdl/stu_area.html. San Diego State University - Curriculum Committee Checklist for Developing Distance Learning Courses. Retrieved from http://wwwrohan.sdsu.edu/~dl/resources/course_cklst.html. San Diego State University Distance Education Policy - Academic Policy and Planning Committee. Retrieved from http://www.rohan.sdsu.edu/faculty/feenberg/sdsudisted.html. Southeastern Louisiana University - Distance Education Policies. Retrieved from http://www2.selu.edu/documents/policies/distedustandards.pdf. Springer A. (2005, March 18). American Association of University Professors (AAUP): Intellectual Property Legal Issues For Faculty and Faculty Unions (2005). Retrieved from http://www.aaup.org/NR/exeres/517C85B6-CC13-4A47-AE3E5C1763713B02.htm. State University College of New York at Buffalo - Electronic Learning Policy. (2001, December 4). Retrieved from http://www.buffalostate.edu/offices/ir/ELearning/elearningpolicy.htm. University of Nebraska eCampus - Tuition and Fees | Online Degree | Online College Degree | Distance Learning | Distance Education | University of Nebraska at Kearney. Retrieved from http://www.unk.edu/acad/ecampus/index.php?id=6205.

Interaction in Distance Education - Upload a Document to Scribd

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Interaction in Distance Education 1 Running head: INTERACTION IN DISTANCE EDUCATION Interaction in Computer Mediated Distance Education Jennifer Maddrell Old Dominion University IDT 846 Distance Learning - Dr. Morrison April 21, 2008 Interaction in Distance Education 2 Interaction Interaction is a well documented construct within distance education literature. A recent search of the Education Resource Information Center (ERIC) database using the keyword “interaction” returned over 46,000 articles. When additional “interaction” descriptors within the ERIC database thesaurus are considered and filtered, as shown in Figure 1, the number of articles balloons to over 71,000. Figure 1. Interaction - ERIC database search. Within these articles are various prescriptions of how to incorporate interaction into the design of instruction, including within the design of distance education. However, a closer review of the literature reveals a range of conceptions of what interaction is and, in turn, how it should be fostered within an instructional setting. Moore (1989) recognized this diversity and observed that the term “interaction” carries so many meanings it is almost useless as a descriptive construct. This prompted a call from Moore for consensus on the distinctions among three types of interaction which he labeled as 1) learnercontent interaction, 2) learner-instructor interaction, and 3) learner-learner interaction. Interaction in Distance Education 3 This paper provides a brief review of how interaction is considered within current distance education literature since Moore’s 1989 call for clarity. The following summarizes how human and non-human interaction types have been considered within the context of computer mediated distant education and examines both the Student-to-Content Interaction Strategies Taxonomy and the Community of Inquiry Model as frameworks for future examination of computer mediated interaction within a distance education setting. Computer Mediated Interaction in Distance Education Literature Of the 71,000 articles about interaction noted above in the ERIC database, just over 4,100 are tagged as “peer reviewed”. Within those, 91 were linked with a “distance education” descriptor. A review of the article abstracts reveals a clear emphasis on human to human interaction, either what Moore terms as learner-learner or learner-instructor interaction. Bannan-Ritland (2002) reports the same finding in a comprehensive literature review of interactivity in relation to synchronous and asynchronous computer mediated communication. Her review yielded a total of 132 articles of which 83 were deemed primary research and 49 were viewed as conceptual. Echoing Moore, Bannan-Ritland describes the challenge of conducting such a review given the lack of common operational definitions and interpretation of interaction in the educational and distance education literature. While Bannan-Ritland’s review revealed multiple definitions and interpretations of interaction, she did find commonalities across what she terms “learner-human level interactions”, such as patterns and amounts of communication, instructor activities and feedback, and other social exchanges. She grouped the research based on how interactivity was defined within the study, including interaction defined by: a) active involvement by the learner, b) patterns of communication among learners and the instructor, c) instructor-learner communication, d) social, Interaction in Distance Education 4 cooperative, or collaborative exchange, and e) instructional activities or technology. Unfortunately, Bannan-Ritland (2002) reports finding no studies during the time period of her review which focused on learner-content interactions in synchronous and asynchronous computer mediated communication and suggests that prior literature reviews focused on the technology as a delivery medium rather than the construct of interactivity. A current search of the ERIC database using “content interaction” as a keyword phrase supports Bannan-Ritland’s findings. 20 articles were returned and only one study is tagged as a peer reviewed research article. Interestingly, within that article, Thorpe and Goodwin (2006) highlight Moore’s conception of learner-content interaction within distance education, as well as Bannan-Ritland’s previously mentioned observation of the lack of learner-content interaction research. Unfortunately, Thorpe and Goodwin’s survey findings from a sample of 4,512 students at the Open University in the United Kingdom provide little insight beyond a snapshot of the instructional content delivery preferences of the surveyed distance learners. Toward an Integrated Framework for Research and Design Given the emphasis on human interaction within recent research on computer mediated communication, it is of little surprise to find a like emphasis on strategies to overcome the physical and time separation to facilitate social interactions during distance instruction. There is pervasive call within the literature for computer mediated social interaction and “community building” within the distance education setting to foster a greater sense of social membership, presence and learner commitment (Rovai, 2002). However, while human interaction (learner to learner and learner to instructor) is often stated as a desired instructional goal within distance education, social interaction in and of itself not a guarantee of cognitive engagement or of meaningful learning (Garrison & Cleveland-Innes, 2005). Interaction in Distance Education 5 Dunlap, Sobel, and Sands (2007) refer to an “ideal of balanced interaction”; one in which learner to content, learner to learner, and learner to instructor interaction are considered. They offer a “Student-to-Content Interaction Strategies Taxonomy” for the contemplation of learnercontent interaction within a distance education setting in which ten content specific interaction category types are mapped to Bloom’s lower level (remember, understand, and apply) and higher level (analyze, evaluate, and create) cognitive process dimensions, as shown in Table 1. Table 1. Student-to-Content Interaction Strategies Taxonomy. Cognitive Process Dimensions Appl Content Interaction Type Remember Understand Analyze Evaluate Create y Enriching       Supportive       Conveyance    Constructive   Triggering    Exploration    Integration    Resolution   Reflective Inquiry   Metacognitive   The content interaction types are a synthesis of the categories presented by Stouppe (1998) and Garrison, Anderson, and Archer (2000) within the Community of Inquiry Model, discussed in greater detail below. Stouppe focuses on four content interactions, including enriching interactions (which allow access to information), supportive interactions (which assist the learner to understand material), conveyance interactions (which demonstrate the concept), and constructive interactions (which require the learner to organize or map knowledge and understanding). In addition, Garrison et al. emphasize interactions which support critical thinking, including triggering interactions(which lead to recognition of a problem), exploration Interaction in Distance Education 6 interactions (which encourage learners to further explore), integration interactions (which facilitate connection of ideas to create solutions), and resolution interactions (which foster application and assessment of solutions). Dunlap et al. included two additional interactions focused on reflective inquiry (requiring deliberation and action) and metacognition (encouraging self-reflection on the learner’s own cognitive process). Dunlap et al. suggest that these content interaction types help to support various cognitive process dimensions. Given Bloom’s established framework which helps designers map learning objectives to cognitive process dimensions, Dunlap et al. propose that their taxonomy of strategies is a means of supporting learning objectives with specific content-interaction strategies. In addition to Moore’s learner-content, learner-learner, and learner-instructor interaction. Anderson (2003) suggests that addition interaction types must be considered and adds three “learner-environment” dimensions of teacher-teacher, teacher-content, and content-content. These six types of interactions are incorporated within the Community of Inquiry Model by Garrison et al. (2000) which recommends an integration of cognitive, social, and teaching presence within a computer mediated distance education setting. According to Garrison et al. (2001), cognitive presence is the ability for learners to construct and confirm meaning most often associated with critical thinking and is linked to the categories of learner-content interaction highlighted previously within Table 1. Social presence is considered the ability of learners to project their own personalities within the distance learning environment as measured in terms of emotion expression, open communication, and group cohesion (Rourke, Anderson, Garrison, and Archer, 2001). In contrast, teaching presence Interaction in Distance Education 7 considers instructional management, including both the design and delivery of instruction (Garrison et al., 2001). The foundation of the Community of Inquiry Model is that neither social interaction alone nor an exchange of information are sufficient, but rather, “quality interaction and discourse for deep and meaningful learning must consider the confluence of social, cognitive, and teaching presence – that is, interaction among ideas, students, and the teacher.” (Garrison and ClevelandInnes, 2005, p. 144). When paired with the Student-to-Content Interaction Strategies Taxonomy proposed by Dunlap et al., a comprehensive framework for future examination of computer mediated interaction within a distance education setting emerges which contemplates multiple levels of both human and non-human interaction. Interaction in Distance Education 8 References Anderson, T. (2003). Modes of Interaction in Distance Education: Recent Developments and Research Questions. In M. Moore and G. Anderson (Eds.), Handbook of Distance Education. (pp. 129-144) NJ: Erlbaum. Bannan-Ritland, B. (2002). Computer-Mediated Communication, E-learning, And Interactivity. Quarterly Review of Distance Education, 3(2), 161. Dunlap, J. C., Sobel, D., & Sands, D. I. (2007). Designing for Deep and Meaningful Student-toContent Interactions. TechTrends: Linking Research & Practice to Improve Learning, 51(4), 20-31. Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2-3), 87-105 Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical Thinking and Computer Conferencing: A Model and Tool to Assess Cognitive Presence. American Journal of Distance Education. Garrison, D. R., & Cleveland-Innes, M. (2005). Facilitating Cognitive Presence in Online Learning: Interaction is Not Enough. American Journal of Distance Education, 19(3), 133. Moore, M. (1989). Three types of interaction [Electronic version]. The American Journal of Distance Education, 3(2). Retrieved from http://www.ajde.com/Contents/vol3_2.htm#editorial. Interaction in Distance Education 9 Rourke, L., Anderson, T. Garrison, D. R., & Archer, W. (2001). Assessing social presence in asynchronous, text-based computer conferencing. Journal of Distance Education, 14(3), 51-70. Retrieved from http://cade.icaap.org/vol14.2/rourke_et_al.html . Rovai , A. (2002). Building Sense of Community at a Distance. International Review of Research in Open and Distance Learning, Retrieved from http://www.irrodl.org/index.php/irrodl/article/viewFile/79/153 Stouppe, J. R. (1998). Measuring Interactivity. Performance Improvement, 37(9), 19-23. Thorpe, M., & Godwin, S. (2006). Interaction and e-Learning: The Student Experience. Studies in Continuing Education, 28(Nov), 203.