Learning, Problem Solving, and Mindtools

Essays in Honor of David H. Jonassen

J. Michael Spector, Barbara B. Lockee, Sharon Smaldino, Mary Herring, J. Michael Spector, Barbara B. Lockee, Sharon Smaldino, Mary Herring

• Publisher: Routledge
• Year: 2013
• ISBN:
  9781136277351
• Edition: 1
• Topic: Didattica
• Subtopic: Didattica generale

Learning, Problem Solving, and Mindtools is inspired by the substantial body of learning research by David H. Jonassen in the areas of mind tools and problem solving. The focus of the volume is on educational technology, especially with regard to how new technologies have facilitated and supported problem solving and critical thinking. Each chapter focuses on a particular aspect of learning with technology and elaborates the implications for the design and implementation of learning environments and activities aimed at improving the conceptualization of problems, reasoning and higher-order thinking, and solving challenging problems.

This collection of scholarly essays provides a highly engaging treatment of using tools and technologies to improve problem solving; multiple perspectives on integrating educational technology to support learning in complex and challenging problem solving domains; guidance for the design of instruction to support problem solving; a systemic account of the relationships between mental models, instructional models, and assessment models; and a look into the future of educational technology research and practice.

1 Mindtools and Problem Solving

An Introduction

J. Michael Spector, Barbara B. Lockee, Sharon E. Smaldino, Mary C. Herring

Learning, Complexity and Problem Solving

When one thinks about the nature of working and living in the twenty-first century, what comes to mind? Of course the answers will vary from person to person, region to region, and situation to situation. For many, the answers are likely to be related, however indirectly, to the problems one encounters or expects to encounter. Typical/generic problems include selecting a career, deciding to get married and have children, purchasing a home or car, planning an event, ending a relationship, resolving a dispute, being productive at work, and so on. Many have argued that such problems have become more challenging and complex in the twenty-first century due to new technologies, globalization, and rapidly changing circumstances surrounding many of the problems we are likely to confront. Not surprisingly, one of the central objectives of education and many instructional programs is to improve problem-solving skills and abilities (Borgman, 2008; Bransford, Brown & Cocking, 2000; Jonassen, 2004, 2006, 2007, 2011; NRC, 2011).

Once one decides that addressing problem solving in an instructional sequence or educational program is critically important, this question arises: what is it that makes some problems especially challenging for different learners? What are the sources of complexity in various problem-solving situations? Some complexity is inherent in a problem itself. For example, understanding all the complexities involved in purchasing a house compared with those needed to balance a checking account. Problems tend to become more complex when the system or situation involves non-linear relationships among some of the system components, when there is internal feedback and when there are delayed effects. For example, in a manufacturing environment when production is faced with a large backlog of orders, one tactic is to pay people to work overtime to meet that backlog. However, if the overtime persists, the result may be that after a short period of improved productivity and backlog reduction, people begin to make mistakes with the result that orders are misplaced and work has to be reaccomplished. In short, what appeared for a short period of time to be a linear improvement in backlog reduction may turn into a non-linear situation resulting in worsening backlog.

Another source of complexity concerns the people involved in a problem situation. A person with limited knowledge of land prices, home inspection, the cost of remodeling, school districts, and city codes would find it very challenging, while a realtor might regard these issues as quite simple. A person’s background and prior experience is clearly relevant to the perceived complexity of a problem situation. Likewise, a person who is distracted by other matters (e.g., a family crisis, an illness, etc.) may not be able to concentrate on the problem at hand which might have otherwise been easily managed.

In addition, there are general limitations to human reasoning, such as the limits on working memory (Miller, 1956). There is also strong evidence that many people do not reason well when non-linear relationships and delayed effects are involved (Dörner, 1996). Couple these facts about the limitations and constraints of human reasoning with the increasing complexity of problems that we are likely to confront, and one can sense that the educational challenges of the twenty-first century are far from trivial.

What can be done to extend reasoning abilities and better cope with the complex problems we are likely to encounter? Given the history and success of the human experience with tools, the notion of tools to extend our problem-solving abilities is a natural course of action. Agriculture tools allowed early civilizations to thrive in one location and abandon nomadic traditions. Manufacturing tools enabled modern civilizations to create healthier and more productive living arrangements. Of course tools have also been used destructively. A tool in and of itself is perhaps value neutral. For now, we want to focus on how tools might extend our problem-solving abilities, which brings us to the domain of cognitive tools, also known as mindtools (Jonassen, 2000; Jonassen, Carr, & Yueh, 1998).

Before discussing powerful mindtools that support and extend our problem solving and critical reasoning abilities, first take a quick look at a simple mind tool so as to develop a common point of reference. Table 1.1 depicts a simple cost estimation for a vacation. This table was created in Word using a formula to automatically calculate the total.

Imagine that one of the two persons involved in this vacation plan brings this simple table to the other person. A discussion begins. Soon other locations are being considered along with a different length of stay and alternative lodging arrangements. The initial table would then need to be recreated for each scenario to compare outcomes. Suppose the couple has a fixed

Table 1.1 Simple mindtool example

Description	Estimated cost
Travel to and from location	$2,000
Lodging at destination	$1,500
Meals and entertainment	$875
Total	$4,375

maximum budget of $5,000 for the vacation and they want to stay within that limit. In such a case, a spreadsheet would be more helpful in exploring alternatives. A spreadsheet will allow multiple types of formulas to be used along with a variety of constants that can easily be changed to support multiple “what if?” analyses. For example, one cell in the spreadsheet might be used for the number of days involved. This cell can then be referred to when calculating the cost of lodging. Moreover, the couple can then manipulate that single cell to see what would happen if they extend the vacation from four to five days, for example. Such a spreadsheet then becomes a valuable extension of the couple’s reasoning repertoire and might enable them to reach a desirable solution more quickly than might otherwise be possible without such a tool. It allows them to externalize their internal mental models using the spreadsheet as a mindtool (Jonassen, 2006).

Use of the computer as a mindtool to construct better mental models is now quite familiar to many people thanks to David Jonassen’s work. Using mindtools to construct technology-mediated model of phenomena can be considered among the most conceptually engaging task that students can undertake (Jonassen, Howland, Marra, & Chrismond, 2008). The next step is to extend this notion of mindtools to more challenging problems and problem domains. As this is done, it is worth noting that many environments such as home, school, and work, have developed and deployed such tools to support various problem-solving tasks. Given that fact, the integration of mindtools into an instructional sequence and throughout an educational system becomes more than merely a good thing to do — it becomes part of responsible education and training in the twenty-first century.

Part 1 of this volume presents three additional contributions that provide a multi-dimensional context for mindtools. In Chapter 2, Seel, Ifenthaler, and Pirnay-Dummer addresses the dimensions of learning, complexity and problem solving from a psychological perspective involving the successive and cumulative development of useful and productive mental models. In Chapter 3, Wilson addresses the dimensions of learning, complexity and problem solving from an instructional design perspective, emphasizing the critical importance of meaningful practice in developing knowledge and understanding. In Chapter 4, Reeves provides a synthesis of these dimen-sions and perspectives as applied to the challenging and complex domain of healthcare.

Representation and Visualization Affordances

Technological innovations for teaching and learning have brought significant advancements in pedagogical approaches, especially since the advent of personal computing technologies. The methods available for the representation of information have evolved to provide a broader array of options in the way that information can be represented and, consequently, engaged with by the learner. The construct that Levie and Dickie (1973) described as media attributes, or features of the instructional delivery system, has been more recently explored as affordances of learning environments (Gibson, 1977; Gaver, 1991; Norman, 1988; Kirschner & Wopereis, in press). Jonassen’s examination of the computer as a mindtool reflects the ability of such technological systems to support learning, in part due to the inherent features of these systems to facilitate different strategies for visual representations of information. On the part of the designer, computers can represent the learning context, supporting the use of problem-based approaches that situate the learner in real-world, meaningful challenges. On the part of the learner, the visual dimension of such systems can reflect interactions with and resulting representations of learning with mindtools.

While the notion of computers as mindtools was not among Jonassen’s initial works related to the use of technology for learning, his early work did explore strategies for the creation of effective learning environments by leveraging the visual features, or affordances, of media to support learning. For example, in his book, The Technology of Text: Principles for Structuring, Designing, and Displaying Text (1982), Jonassen presented message design guidance for the use of various types of text (printed, electronic, teletext), as well as design principles for supplemental visual information such as diagrams, charts, and so on. The principles featured in this book have continuing relevance to current message design needs, particularly with the proliferation of distance learning, so much of which is delivered primarily through text-based information. Researchers and practitioners alike still examine and employ aspects of this important work — see Chapter 8 by Wijekumar and Meyer.

The affordances of technologies to represent visual understanding continue to develop, as innovations have brought forth new ways to support instructional design and learner engagement. In Chapter 5, Warren and Wakefield examine how educational games provide constructivist learning environments that align with Jonassen’s notion of mindtools that support critical thinking and, therefore, cognition. Kirschner and Wopereis contend in Chapter 6 that Web 2.0 tools not only facilitate collaborative, constructivist learning activities for students, but they can also provide the infrastructure for networked communities of practice, a newly conceived mindtool for teacher professional development.

In Chapter 7, Laffey, Schmidt, and Galyen advocate the use of three-dimensional virtual environments (3D VE) as experience tools that would support authentic learning experiences that are at the same time social, embodied, meaningful and playful. Also related to the social affordances of technological learning environments, As technologies for learning continue to evolve, so will mechanisms to design and assess visual representations of knowledge. In Chapter 9, Tan discusses potential ways to advance the foundational research to which Jonassen (2000, 2004, 2006) contributed so significantly in this area, asking us to examine our own beliefs and ideologies related to the design of technology-supported, problem-based learning environments.

In sum, Part 2 of this volume provides a reminder of how very important support for representation and visualization are in the process of coming to know and understand. Jonassen’s many publications have helped us learn this valuable lesson.

Problem Solving and Critical Thinking

In his many published works, David Jonassen has contributed much to the context of problem solving and the critical thinking relevant to the process of solving problems. In Part 3, the five authors have focused on issues associated with these elements.

In Chapter 10, Michael Hannafin explores the connection between theory and design in addressing learning needs. His focus on the implications of differences in theory and epistemology demonstrates their impact on learning and design of instruction. In Chapter 11, Woei Hung advocates for the integration of problem-based learning (PBL) as an instructional strategy to challenge students to address real-world issues. The suggestion is that PBL provides students of any age the opportunity to explore a learning problem and develop approaches to resolution of that circumstance. In Chapter 12, Lee and Murcia offer a view of problem solving and elements of conceptual change. They propose that when students engage in problem solving they become aware of the inconsistencies in their own thinking and subsequently gain a better understanding of their own way of thinking and learning needs. In Chapter 13, Land, Smith, and Zimmerman offer the use of computer tools to be adapted or created to extend thinking and problem solving. Using Jonassen’s (2000) model of mindtools, they apply that model to three examples where mobile technologies can serve as the vehicles to support student thinking and creative learning in all settings. In Chapter 14, Brian Belland focuses on Jonassen’s work pertaining to illstructured problems and how students need to apply argumentation in their thinking process as they try to resolve those problems (Jonassen & Kim, 2010). Without simple solutions, students need to develop their skills in preparing arguments to support resolutions.

In each chapter of this section of the book, the interrelated themes of problem solving and critical thinking are...