Advice from Shaffer

The Internet will (or has) render(ed) the memorization of declarative knowledge obsolete. In the future, only the ability to be innovative in professional practices will be of value. The Internet enables virtual collaboration within real communities to develop these practices. The practices will be built through epistemic games.

The key is adoption by the stakeholders:

  • the new curriculum which must be developed
  • the teachers who must learn to facilitate these epistemic games
  • the school administrators who must support the teachers
  • the parents who must understand the value of this approach

“What about the students?” you ask. They’re already ready.

The critical topics to explore include:

  • How can we build epistemic games cheaply but with the rich multimedia needed to engage a visual generation raised on television?
  • How can we teach our teachers to use epistemic games to replace their familiar scope and sequence charts, not merely add the games as a diversionary activity?
  • How can we convince our school boards to abandon the practice of teaching to standardized tests and instead focus on teaching students to be the professional innovators through epistemic games?
  • How can we demonstrate to parents that the future valuable practices are what we should be teaching?
Advertisements

Games & Learning – Summary

Shaffer, D. (2006). How Computer Games Help Children Learn. New York: Palgrave Macmillan.

Chapter 1

  • Rules define games (and play); the need for authenticity implies that writing the rules is the most difficult aspect of game creation.
  • Some roles make players care about winning; other roles make players care about self-efficacy. Because roles (and thus end-states) differ, rules vary with roles. This role-rule pairing creates the narrative, another difficult task.

Chapter 2
The knowledge gained in the game persists because it’s tied to a particular epistemology. Computers don’t simply store symbols, but also process them and thus will lead to a virtual culture based on symbol processing.

Chapter 3
All games are microworlds, and players come to those microworlds with a set of beliefs, make decisions based on those beliefs, and receive responses from the simulation which bring those beliefs to the surface, challenge them, and then refine the beliefs.

Knowing how (procedural knowledge) is what games teach; knowing what (declarative knowledge) is what books teach. The practicum process involves:

  • doing things as a professional (action)
  • discussing what happened with the community (reflection on action)
  • repeating this iterative cycle until the process is internalized (reflection in action

Chapter 4
Games must impose obstacles that are neither too easy (boring) nor too hard (frustrating) to create a condition of flow; levels should be barely achievable. For players to even try to overcome obstacles, they must care, and thus games must provide motivation. Making a game fun provides intrinsic motivation. Playing by the rules is fun, and fun offers self-efficacy–players feel they are able to master the game.

Chapter 5
Symbolic knowledge is developed in solving one problem can be used to solve other analogous problems. Schematic knowledge involves combining facts (declarative) and problem-solving strategies (procedural) knowledge to solve problems. Situated cognition, however, views all activity as part of a community of practice where newcomers learn through legitimate peripheral perception.

For the value of games to extend beyond the game itself, epistemic frames (which exist partly in the mind of the players and partly in the structure of the game) provide the “grammar” of the local culture of a community of practice. These frames are a level of description between and across the symbolic, schema and community views of learning.

Simulations and games are related but distinct:

  • simulations do not have epistemic frames
  • all games are based on simulations
  • games create a virtual world using a simulation
  • epistemic games create the epistemic frame of a community by recreating the process by which individuals develop that community

Chapter 6
Designing epistemic games is challenging:

  • games are built on simulations which are simplified (thus distorted) views of the world
  • simulations without a community of practice and without the opportunity for reflection and feedback offer no real context
  • professions are built on practices which are evolved rather than designed; these professional practices do not offer “general principles of learning that can be used anywhere” but instead provide markers
  • “learning takes place only as part of a coherent system” and thus we will fail if we merely extract professional practices (or game elements) and drop them into existing curricula

Another Agenda

Sprague, D. (2006). Editorial: Research Agenda for Online Teacher Professional Development. Journal of Technology and Teacher Education. 14 (4), pp. 657-661. Chesapeake, VA: AACE. Retrieved from http://www.editlib.org.ezproxy.lib.utexas.edu/p/22827.

Like Dede’s article, this editorial sets out a clear vision for the consideration of online professional development for teachers. However, unlike Dede’s proposal, Sprague provides a practical rather than a philosophical rationale:

  • access to experts (not place-bound)
  • time for reflection (not time-bound)
  • possible solution for the retention issue (community involvement)

However, Sprague also acknowledges limitations in moving to online TPD (Teacher Professional Development):

  • online facilitators need training
  • initial costs to build the online resources
  • ongoing costs to sustain the learning community
  • existing programs may view online offerings as competition or diversion, rather than  opportunity

In looking to the future of online education in general (not only TPD) Sprague mentions the need to help new teachers learn how to teach online and thus connects online education with TPD: delivering professional development to teachers online is an inductive way to show that teacher how to teach online.

Although Sprague’s concerns about which emerging technologies will have the most impact or the correct balance in hybridization are somewhat irrelevant (because the technologies will continually change and because the balance will be determined through research), her agenda, like her vision, is practical:

  • what is the depth and scope of online TPD needed to have an impact?
  • even if there is an impact, what other factors might prevents change (such as the school environment or the conflicting demands of teaching 21st century skills with NCLB)?
  • what are the patterns of change we should observe in teachers to determine what’s working?

IM distracted

Levine, L., Waite, B., & Bowman, L. (2007). Electronic Media Use, Reading, and Academic Distractibility in College Youth. CyberPsychology & Behavior 10(4). pp. 560-566.

While this article supports the popular notion that instant messaging interferes with academic tasks such as reading textbooks, the flawed design call the results into question. The authors equate statements such as, “I rarely do the assigned readings for my classes” with being distracted from academic tasks. In fact, failing to do the assigned readings could be attributed to character flaws, laziness, boredom, or a host of other non-IM related causes.

The authors report that a typical IM session lasts 75 minutes. Personal experience suggests this is exaggerated if the figure is taken to mean that 75 minutes of focused time is devoted to the average IM session. While users may indeed report that an IM service is running for 75 minutes per session, the surveys fail to probe the self-reported results to determine the number of messages, a more accurate  indicator of  potential IM attention disruption.

Selective reporting of results further demonstrates bias. For example, the authors report that distractibility was “significantly predicted by the amount of IMing.” However, they do not report that responding quickly to IMs, an obvious indicator of distractibility, was less of a predictor than listening to music. Similarly, they cite research that found television viewing increased attention problems; however, the authors own data shows television has less impact than music, and that playing video games decreases academic distractions.

The authors claim three possible explanations for IM’s interference with academic pursuits:

  • IM takes time away from studies
  • IM directly interferes with studies
  • IM changes students into superficial multitaskers

The authors endorse this third possibility by spending additional time exploring its plausibility by reference to other studies. However, even if the definition of academic distractibility were accurate, even if the design has been observational rather than anecdotal, and even if the results had been reported fully and fairly, additional explanations exist for the cause-effect relationship the authors falsely claim to have proven.

Internet flow: the drug of procrastination

Thatcher, A., Wretschko, G., & Fridjhon, P. (2008). Online flow experiences, problematic Internet use and Internet procrastination. Computers in Human Behavior 24. pp. 2236-2254.

This article explores the relationships among three separate behaviors:

  1. problematic Internet use (PIU): viewed through Bandura’s theory of self-regulation of excessive behaviors “that may periodically arise and that may, over time , be self-remedied”; this remedy depends on a person’s belief in his ability to stop, and the absence of this belief causes the person to seek an escape from reality.
  2. Internet procrastination: delaying the start or completion of a task; procrastination is caused by difficult or boring tasks, by anxiety from task evaluation, or by tasks with a lack of control over completion.
  3. Flow on the Internet: a state of pleasure that occurs when skills closely match challenges.

Rather than stretching the connections, the authors confine their research to three hypotheses:

  1. that PIU and Internet procrastination are strongly correlated
  2. that PIU and flow are weakly uncorrelated (based on the finding that addictive behavior is not fun and thus does not produce a flow state)
  3. that immersive Internet activities will have higher levels of PIU and flow

The results are expected but provide additional insight into the connections:

  1. PIU and Internet procrastination are strongly correlated, although that relationship is unaffected by relationships with flow
  2. surprisingly, PIU and flow are weakly correlated (although this could be because they share many of the same qualities); procrastination may be a connector between the two
  3. immersive Internet activities are the best predictors of PIU, flow, and procrastination while email and general browsing are not predictors. The best flow predictor was chat, although the “immersive” classification of activities such as blogging (a reflective and often solitary endeavor) seems questionable.

Procrastination has the greatest impact among the variables; the next greatest was the amount of time spent online per session. However, before generalizing the results, the authors caution that the study:

  • was conducted over the Internet and advertised from a South African website
  • was based on self-reported survey results which may be biased toward Internet users

At the same time, the study clearly demonstrates a relationship among the activities. The authors suggest future research directions–mapping flow, skill and challenge to specific activities, and distinguishing PIU from other addictive behaviors such as workaholism–which may shed additional light.

The difficulty of multitasking

Carrie, L., Cheever, N., Rosen, L., Benitez, S., & Chang, J. (2009). Multitasking across generations: Multitasking choices and difficulty ratings in three generations of Americans. Computers in Human Behavior 25. pp. 483-489.

The authors consider an important issue–how multitasking differs among age groups–but fail to adequately limit their definitions or explore deeper hypotheses. For example, they refer to an earlier study that defines the most common multi-tasking behavior among 14-16 year-old youth as, “listening to audio media while travelling,” an activity that hardly seems to fit; the activity would be appropriate to include if it were driving while listening to music among 17-19 year-olds. The hypotheses they consider seem superficial:

  • that younger generations will multitask more
  • that generations will choose different tasks to combine
  • that  younger generations will find it easier to multitask
  • that generations will find different task combinations difficult

The authors measure daily task activity by generation and self-reported combinations (and the corresponding difficulties of those combinations) of tasks by generation. The findings are predictable:

  • younger generations report more multitasking
  • all generations combine the same tasks (which may be attributed to cognitive limits)
  • the oldest generation reported more combinations to be difficult
  • all generations found the same combinations difficult (which again may be attributed to human limitations)

The primary problem with the research is the complete reliance on self-reporting. In their defense, the authors list three limits on the research:

  1. no distinction was drawn between task switching and parallel processing
  2. the study measured only decisions made about multitasking, not the actual ability to multitask (task congruence, not task performance)
  3. future research may show common costs of task switching regardless of generation (which could lend credence to the claim of cognitive limits)

Online Teacher Professional Development

Dede, C., Ketelhut, D., Whitehouse, P., Breit, L., & McCloskey, E. (2009). A Research Agenda for Online Teacher Professional Development. Journal of Teacher Education 60(1). pp. 8-15.

While the oTPD acronym seems contrived, the proposed models and research recommendations offer a compelling vision for this critical endeavor. Echoing Bransford’s analysis, the authors view existing professional development as superficial and “unable to provide (the) ongoing support” needed to sustain community-based systemic learning. Under an NSF grant, the authors are studying three models for long-term impact on teaching:

  • multiuser virtual worlds
  • augmented realities through wireless mobile devices
  • social tagging by teachers to generate mental models of the profession

In order to chart a way forward, the authors first conducted a meta-analysis of 40 research studies of online TPD which showed four general categories of investigation:

  1. program design
  2. program effectiveness
  3. program technical design
  4. learner interactions

Further analysis showed the following purposes underlying the studies:

  • 39% – program evaluation design
  • 22% – how best to teach
  • 20% – content and skills
  • 12% – improvement enablers
  • 7 % – desired educational improvement

These percentages clearly illustrate the underlying problem: the emphasis is on evaluating effectiveness in order to justify programs, rather than a focus on learning improvement through an analysis of design. The authors then outline a series of questions to guide future studies; a simplification of the proposed agenda includes:

  • Scalable and sustainable programs that permanently transform practice
  • Strategies that merge practical and theoretical needs
  • Models that include formative methodologies such as DBR (Design Based Research) and summative methodologies such as clinical trials
  • Designs that clearly pose questions and define assumptions
  • Methodologies that take advantage of the data-gathering possibilities inherent in online instruction and balance the self-reporting nature of most studies
  • Communicating results through a centralized knowledgebase
  • Build on results from other professional development practices

As a community, we can anticipate practical and applicable results from future research guided by these questions.