Communication design andtheories of learning

Dr. Brad MehlenbacherAdult & Higher EducationNC State Universitybrad_m@unity.ncsu.edu www4.ncsu.edu/~brad_m

ACM SIGDOC 2008Lisbon, Portugal

The work of communication designers

Communication designers produce information and information spaces that explain, describe, elaborate on, guide, instruct, support, and complete the technologies that others use

The information spaces that we design and engage in present themselves to us as ill-structured problem domains.

Mehlenbacher, B. (under review). Instruction and technology: Designs for everyday learning. Cambridge, MA: MIT Press.

Adopted from:

Working in ill-structured . . .

Ill-structured problem domains involve simultaneous interactive involvement of multiple, wide-application conceptual structures (multiple schemas, perspectives, organizational principles, etc.)

Ill-structured problem domains involve patterns of conceptual incidence and interaction that varies substantially across cases nominally of the same type (cases involve across-case irregularity).

Spiro, R. J., Feltovich, P. J., Jacobson, M., & Coulson, R. L. (1992). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. In T. M. Duffy & D. H. Jonassen (Eds.), Constructivism and the technology of instruction: A conversation (pp. 57-75). Hillsdale, NJ: Lawrence Erlbaum.

Adopted from:

. . . information spaces

Ill-structured problem domains are unstable and demand flexibility, a creative ability to organize across single data points and to understand, argue, and evaluate categorically

Ill-structured problem domains require strategies for carrying what has been learned into new situations and contexts, for managing trade-offs, and for turning understanding into actions.

Fischer, G. (2000). Lifelong learning — More than training. Journal of Interactive Learning Research, 11 (3/4), 265-294.

Adopted from:

A typography of work

March, J. G., & Simon, H. A. (1958). Organizations. NY, NY: Wiley.

Adopted from:

Communication design tasks

Collecting, sorting, analyzing, interpreting, designing, reporting data, collaborating, communicating, interacting, negotiating

Generating representations, accessing and navigating information, identifying, explaining, and analyzing phenomena, taking positions, communicating

Kozma, R., Chin, E., Russell, J., & Marx, N. (2000). The roles of representations and tools in the chemistry laboratory and their implications for chemistry learning. Journal of the Learning Sciences, 9 (2), 105-143.Mayer, R. E. (2001). Multimedia learning. NY, NY: Cambridge UP.Unsworth, J. (2000). Scholarly primitives: What methods do humanities researchers have in common, and how might our tools reflect this? Humanities computing symposium: Formal methods, experimental practice. London, England: King’s College. Available online: http://www.iath.virginia.edu/~jmu2m/Kings.5-00/primitives.html

Adopted from:

Discovering, annotating, comparing, referring, sampling, illustrating, representing

Selecting, organizing, integrating, comparing, generalizing, classifying

Inventing, judging, deciding, evaluating.

General problem-solving tasks for the 21st century

Allen, B. L. (1996). Information tasks: Toward a user-centered approach to information systems. San Diego, CA: Academic P.Association of College & Research Libraries (ACRL). (2000). Information literacy competency standards for higher education. Available online: http://www.ala.org/ala/acrl/acrlstandards/informationliteracycompetency.htmNorman, D. A. (1990). The design of everyday things. NY, NY: Basic.

Adopted from:

Ill-structured problem solving

Articulate problem space and contextual constraints Identify and clarify alternative opinions, positions,

and perspectives of stakeholders Generate possible problem solutions Assess the viability of alternative solutions by

constructing arguments and articulating personal beliefs

Monitor the problem space and solutions options Implement and monitor the solution, and Adapt the solution.

Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45 (1), 65-94.

Adopted from:

What we know about learning

Information + Comprehension (attention, selection, working memory, cognitive workload)

Representation + Integration with existing and available knowledge structures (encoding, strategies for potential storage in long-term memory, information mapping, schemata, and interaction with external resources)

Anderson, J. R. (1995). Learning and memory: An integrated approach. NY, NY: Wiley.Bransford, J., Brown, A. L., Cocking, R. R., & National Research Council (2000). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy P. Available online: http://www.nap.edu/openbook/0309065577/html/index.htmlPerkins, D. N. (1993). Person-plus: A distributed view of thinking and leanring. In G. Salomon (Ed.), Distributed cognition: Psychological and educational considerations (pp. 88-110). Cambridge, England: Cambridge UP.

Adopted from:

Retrieval + Development of new connections between the new information and the existing state of understanding (reviewing, associative reasoning, mental models, conceptual organization, and interaction with external resources), and

Construction + Elaboration toward a richer understanding of the subject matter, leading to expert understanding and/or behaviors (practice, reorganization of material for problem setting, plan and goal development, propagation, and situational exigencies).

What it means to understand technology

Understanding technology "depends on your relationship to it" (p. 109). Understanding differs depending on whether you are a programmer, a teacher, a document designer, an administrator, an author of how-to technology books, a parent, an instructional designer, an academic researcher studying technology, or a politician

Understanding is critical to acting intelligently in relation to technology. What it means to understand technology depends on who you are and how intelligently you are able to act in relation to technology, managing technical specialists, deciphering research on technology, guiding learners as they become familiar with specific types of technology, or supporting technical activities.

Adopted from:

Bereiter, C. (2002). Education and mind in the knowledge age. Mahwah, NJ: Lawrence Erlbaum.

Interest, context, and understanding

Understanding interacts with interest. That is, it is difficult to imagine someone who has no interest in technology being able to claim an understanding of it

Understanding technology requires some understanding of systems theory and logic, the social and cultural forces that shaped and are shaped by technology, and so on

Just as "no single correct, complete, or ideal understanding" (p. 110) of technology can exist, there can be identifiably incorrect understandings

Conversations about technology generally emphasize the construct or artifact itself, its importance, foundations, strengths and limitations, and so on.

Adopted from:

Bereiter, C. (2002). Education and mind in the knowledge age. Mahwah, NJ: Lawrence Erlbaum.

Involvement and understanding

Understanding is often conveyed through narratives containing key ideas such as progress, innovation, adoption, social and cultural influences, and so on. Incomplete or incoherent narratives reveal problems with understanding

A deep understanding of technology requires knowledge of deeper things related to it such as state-of-the-art developments and historical developments of fundamental machinery and systems

Insightful problem solving is possible with deep understanding

Deep involvement with technology, for various audiences, situations, and contexts, is required for deep understanding.

Adopted from:

Bereiter, C. (2002). Education and mind in the knowledge age. Mahwah, NJ: Lawrence Erlbaum.

Cognitive and social learning

De-contextualizes knowledge Behavioralists in disguise Advocate mind-as-container myth Ignore context/situation Empirical to a fault.

Simon, H. A. (1969, 1981). The sciences of the artificial. Cambridge, MA: MIT P.

Adopted from:

Over-situate learning Non-pragmatic and difficult to evaluate Ignore individual learning Qualitative and impossible to

generalize.

"The proper study of mankind has been said to be man. But I have argued that man — at least the intellective component of man — may be relatively simple, [but] that most of the complexity of his behavior may be drawn from man’s environment. . . ."

Sociocognitive . . .

Anderson, J. R., Greeno, J. G., Reder, L. M., & Simon, H. A. (2000). Perspectives on learning, thinking, and activity. Educational Researcher, 29 (4), 11-13.

Adopted from:

"The cognitive and situative perspectives also provide valuable complementary analyses of . . . learning. For example, in mathematics education the cognitive perspective provides important analyses of information structures in conceptual understanding and procedures that are needed for students to succeed in the tasks emphasized in most mathematics curricula. . . The situative perspective provides important analyses that emphasize students’ participation in socially organized activities of learning, including patterns of classroom discourse and the opportunities to learn how to participate in the learning practices that their classrooms support. . . .

. . . learning

Anderson, J. R., Greeno, J. G., Reder, L. M., & Simon, H. A. (2000). Perspectives on learning, thinking, and activity. Educational Researcher, 29 (4), 11-13.

Adopted from:

A more complete cognitive theory will include more specific explanations of differences between learning environments, considered as effects of different contexts, and a more complete situative theory will include more specific explanations of individual students’ proficiencies and understandings, considered as their participation in interactions with each other and with material and socially constructed conceptual systems"

Deeper learning principles

Carmean, C., & Haefner, J. (2002). Mind over matter: Transforming course management systems into effective learning environments. Educause Review, November/December, 27-34.

Adopted from:

Alternative views of the same learning

Mehlenbacher, B. (under review). Instruction and technology: Designs for everyday learning. Cambridge, MA: MIT Press.

Adopted from:

A Sociocognitive orientation provides opportunities for framing instructional and communication information spaces as both profoundly personal and individual and intensely sociocultural in nature.

Perspectives on learning

Csikszentmihalyi, M. (1996). Creativity: Flow and the psychology of discovery and invention. NY, NY: HarperCollins.

Evans, V. (2004). The structure of time: Language, meaning and temporal cognition. Amsterdam, Netherlands: John Benjamins.

Langer, E. J. (2000). Mindful learning. Current Directions in Psychological Science, 9 (6), 220-223.

Adopted from:

"When we ignore perspective, we tend to confuse the stability of our mind-sets with the stability of the underlying phenomenon: All the while things are changing and at any one moment they are different from different perspectives, yet we hold them still in our minds as if they were constant"