The Use of Simulated Dialogue Metaphor to Model Expert Problem Sovling Processes to Improve Students' Knowledge of Research Design

  • Upload
    mcsm1th

  • View
    214

  • Download
    0

Embed Size (px)

Citation preview

  • 8/14/2019 The Use of Simulated Dialogue Metaphor to Model Expert Problem Sovling Processes to Improve Students' Knowledge of Research Design

    1/4

    1

    The Use of Simulated Dialogue Metaphor to Model Expert Problem Solving

    Processes to Improve Students Knowledge of Research Design

    Wei-Chen Hung, Thomas J. Smith, & M Cecil Smith

    Northern Illinois University

    Abstract

    This study used a simulated dialogue metaphor design framework as the design method to

    develop a scenario-based interactive learning environment that draws a connection between

    cognitive apprenticeship based instructional strategies and user-centered interface design.

    Several system usability evaluations were carried out to identify students perceptions toward

    the system. Results showed that the initial system prototype provided an effective framework

    for guiding students through their problem-solving process. Presentation will include

    demonstration of the system and discussion of the evaluation results.

    Introduction

    Current studies into the ways in that technology can be used to scaffold problem solving and reasoning

    skills raise several research-worthy issues involving both cognitive science and visual literacy. It is

    widely recognized that the pedagogical emphasis in problem solving is on the process of learning, rather

    than the mere acquisition of facts. This process of learning is concerned with students reasoning skills

    (e.g., metacognition, reflection, and critical thinking) and how they test their understanding of given

    problems. Numerous studies have shown the benefits of visuals in learning (e.g., Braden, 1996; Croft,

    2001; Dwyer & Baker, 2001; Mathewson, 2004). Research also has shown that the degree of studentshigher level thinking and how it is applied may vary depending on the context of the situation (Berardi-

    Coletta, Buyer, Dominowski, & Rellinger, 1995; Hartman, 2001).

    The greatest effect on the reasoning process is produced by providing information at precisely the time

    that an individual becomes aware of the need for the information (Cruickshank & Olander, 2002; Edelson

    Gordin, & Pea, 1999). Technology can provide a visual tool through which scaffolding (e.g.,

    metacognitive prompts, performance feedback) can be provided as needed. This scaffolding can help

    learners clarify learning tasks, understand meanings and concepts, draw inferences, apply existing

    knowledge to reach goals, look for relationships, reformulate information in their own terms, and monitor

    progress toward a solution. By integrating scaffolding strategies into a scientific reasoning framework, we

    create an opportunity to increase learners self-directed learning which, as shown by Gourgey (1998), will

    promote achievement in learners problem-solving and reasoning skills.

    A number of technological applications have been employed to increase students learning within

    research methods courses. These applications have included the design of web-based labs for students

    to work on problems in psychology courses (Sommer & Sommer, 2003), use of clip art to demonstrate

    various aspects of classification systems (Abramson, French, Huss, & Mundis, 1999), applications of

    national data sets on CDs to teach about statistical analysis (Ailinger, Howard, & Choi, 1997; Messecar,

    Van Son, & OMeara, 2003), and computer simulations that help student learn statistics (Lajoie, 2000) .Interactive software programs that feature graphics (Hatchette, Zivian, Zivian, & Okada, 1999), and

    online hypertext-based tutorials (Koch & Gobell, 1999), also have been used to demonstrate statistical

    concepts with good success. Generally, these technology solutions focus on relatively narrow skill or

    knowledge areas, rather than fostering students reasoning and critical thinking skills. Therefore, a need

  • 8/14/2019 The Use of Simulated Dialogue Metaphor to Model Expert Problem Sovling Processes to Improve Students' Knowledge of Research Design

    2/4

    2

    remains for technological applications that can be used to scaffold problem solving and reasoning skills.

    Well-designed interactive learning system can provide the requisite instructional tools that provide the

    cognitive supports for students to increase their knowledge and understanding of these thinking skills.

    The design framework

    The system designed in this study, REsearchMentor, used a simulated dialogue metaphor design

    framework (Language Development and Hypermedia Research Group, 1992) to provide support forlearners as they work through a sequence of problem activities. In the case of research methods, the

    activities pertain to the conceptualization, planning, and design of a research study appropriate for the

    behavioral and/or social sciences. Cognitive scaffolding refers to the provision of support to learners thatenables them to develop problem-solving independence. The use of cognitive scaffolding within a

    simulated dialogue metaphor design framework may include diverse features such as an appropriate

    sequences of queries, prompts and examples that anchor students learning, hints that lead students

    towards correct responses; definitions of terms and constructs provided in a glossary of terms; and

    animated sequences and audiovisual presentations.

    REsearchMentoris designed to be learner-centered, a feature that promotes higher-order learning andproblem solving (Kommers, Jonassen, & Mayes, 1991; Lajoie, 2000; Jonassen, 2000). It contains

    cognitive scaffolds that support learners acquisition of basic concepts in research methodology. Such

    scaffolds take the form of hints, explanations, corrective feedback, and helpful reminders. Scaffoldsprovide a form of temporary support that facilitate learners knowledge acquisition and skill development.

    The fully functional REsearchMentorwill include a series of diverse research simulations, videodemonstrations, and animations that enable learners to observe, act, problem-solve, and learn. Learners

    can reflect upon and articulate the common aspects of expert practices, as well as translate and generalize

    to a variety of situations and problems. REsearchMentoralso provides learners with a cognitive map thatclosely models an expert approach to planning and designing social sciences research projects.

    Purpose of the study

    The purpose of this study was to investigate how the use of dialogue-based simulation that incorporates

    visual metacognitive prompts with an inductive design metaphor facilitates the process of students

    reasoning and critical thinking skills as well as content acquisition. Specifically, we were interested in

    learning how the proposed design approach of such a tool would provide a means for students to emulatethe thought processes of experts when solving problems. These thought processes include elements such

    as reactions and perceptions toward the dialogue-based simulation, approaches taken to find cluesassociated with a problem; the reasoning processes used in selecting solutions, and overall strategies for

    developing a research design for a novel situation.

    Formative Evaluations of the REsearchMentorPrototype

    Evaluations of the system prototype have been completed by students enrolled in two educationalresearch courses. These two classes were graduate courses in research methods (a teacher action research

    seminar and an introductory course in educational research). The purpose was to verify that the proposed

    design strategies (simulated dialogue metaphor and metacognitive prompts) were instructionally sound

    and appropriate. The process of formative evaluation began with a short introduction of the design

    concept of the system, then went on to a demonstration of the system with emphasis on the instructionalstrategies used in its functionality. After the demonstration, the researchers asked participants to

    comment on the system's contents and design structure as well as its technical accuracy. The data

    gathered were used to refine and enhance the functions of the system, so that it was workable and could

    be further evaluated by the students.

    During the evaluations, participants commented that the system provided an effective framework for

    guiding them through their problem-solving process. One of the most helpful aspects of the tool,

    according to the participants, was that the framework facilitated the project group members to develop a

  • 8/14/2019 The Use of Simulated Dialogue Metaphor to Model Expert Problem Sovling Processes to Improve Students' Knowledge of Research Design

    3/4

    3

    shared understanding of the project process and nomenclature, which made both the project task and

    communication easier. Another useful aspect of the tool was that it provided a starting point for students

    to comfortably begin solving problems, much like a scaffold in that students can step through the

    problem-solving process without feeling lost or overwhelmed by the complexity of problem.

    References

    Abramson, C.I., French, D.P., Huss, J., & Mundis, M. (1999). Classification laboratory: A

    computer program using clip art to demonstrate classification. Teaching of Psychology, 26(2),135-137.

    Ailinger, R.L., Howard, L., & Choi, E. (1997). Using national data sets on CD-ROM to teach

    nursing research.Image: Journal of Nursing Scholarship, 29(1), 17-20.

    Berardi-Coletta, B., Buyer, L. S., Dominowski, R. L., & Rellinger, E. R. (1995). Metacognitionand problem solving: A process-oriented approach. Journal of Experimental Psychology:

    Learning, Memory, and Cognition, 21(1), 205223.

    Braden, R. A. (1996). Visual Literacy. In D. H. Jonassen (Ed.),Handbook of research for

    educational communications and technology (pp. 491520). New York: Macmillan. Brown, J. S., Collins, A. & Duguid, P. Situated cognition and the culture of learning.

    Educational Researcher, 17, 32-42. 1989

    Cruickshank, B. J., & Olander, J. (2002). Can problem-based instruction stimulate higher order

    thinking? Converting an instrument analysis lab. Journal of College Science Teaching,31(6),

    374377.

    Croft, R. S. (2001). Digital enhancement of photographic illustrations for concept learning in

    nature. In R. E. Griffin, V. S. Williams, & J. Lee (Eds.),Exploring the visual future: Art design,science, & technology (pp. 6975). International Visual Literacy Association.

    Dwyer, F. M. & Baker, R. (2001). A systematic meta-analytic assessment of the instructional

    effects of varied visuals on different types of educational objectives. In R. E. Griffin, V. S.

    Williams, & J. Lee (Eds.),Exploring the visual future: Art design, science, & technology (pp.

    129134). Blacksburg, VA: The International Visual Literacy Association. Edelson, D. C., Gordin, D. N., & Pea, R. (1999). Addressing the challenges of inquiry-based

    learning through technology and curriculum design.Journal of the Learning Sciences,8(34),391450.

    Gourgey, A. F. (1998). Metacognition in basic skills instruction.Instructional Science, 26, 8196.

    Hartman, H. J. (2001). Developing students metacognitive knowledge and skills. In H. J.

    Hartman (Ed.), Metacognition in learning and instruction: Theory, research and practice. (pp.3368). London: Kluwer Academic Publishers.

    Hatchette, V., Zivian, A.R., Zivian, M.T., & Okada, R. (1999). STAZ: Interactive software for

    undergraduate statistics.Behavior Research Methods, Instruments, & Computers, 31(1), 19-23.

    Jonassen, D. (2000). Computers as mindtools for schools : Engaging critical thinking. UpperSaddle River, N.J. : Merrill.

    Koch, C., & Gobell, J. (1999). A hypertext-based tutorial with links to the Web for teachingstatistics and research methods.Behavior Research Methods, Instruments, & Computers, 31(1),7-13.

    Kommers, P., Jonassen, D. & Mayes. J. T. (Eds.). (1991). Cognitive tools for learning. New

    York: Springer-Verlag.

    Language Development and Hypermedia Research Group. (1992). Bubble dialogue: A new toolfor instruction and assessment.Educational Technology Research and Development, 40 (2), 59-

    67.

  • 8/14/2019 The Use of Simulated Dialogue Metaphor to Model Expert Problem Sovling Processes to Improve Students' Knowledge of Research Design

    4/4

    4

    Lajoie, P. (Ed.). (2000). Computers as cognitive tools: No more walls. Hillsdale, N.J. : LawrenceErlbaum Associates.

    Mathewson, J. (2004). The signs of semiotics for science classrooms. In R. E. Griffin, J. Lee, &

    S. Chandler (Eds.), Changing tides (pp. 183189). Blacksburg, VA: International Visual LiteracyAssociation.

    Messecar, D.C., Van Son, C., & OMeara, K. (2003). Reading statistics in nursing research: A

    self-study CD-ROM module.Journal of Nursing Education, 42(5), 220-226. Sommer, B.A., & Sommer, R. (2003). A virtual lab in research methods. Teaching of

    Psychology, 30(2), 171-173.