Jonassen & Reeves (1996). Learning with technology: Using computers as cognitive tools.

Jonassen, D. H., & Reeves, T. C. (1996). Learning with technology: Using computers as cognitive tools. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (1st ed.). Retrieved from

“Cognitive tools refer to technologies, tangible or intangible, that enhance the cognitive powers of human beings during thinking, problem solving, and learning. Written language, mathematical notation, and, most recently, the universal computer are examples of cognitive tools.” (p 693)

“We regard the ‘technology as instructional communications’ perspective (see Chapter 4), although admittedly widespread throughout education and training, to be inherently flawed because it fails to recognize learners as active constructors of knowledge (Duffy & Jonassen, 1992; see Chapters 7 and 23).” (p 693)


“Instead of specialists such as instructional designers using technology to constrain students’ learning processes through prescribed communications and interactions, the technologies are taken away from the specialists and given to learners to use as media for representing and expressing what they know.” (p 694)

“At least part of this failure stems from the overly restrictive perspective of students as perceivers or recipients of educational communications that characterizes the research in this field.” (p 694)


“Considered together, constructivism and its attendant principles constitute a strong rationale for using technology as cognitive tools.” (p 695)

[24.3.1 Knowledge Construction, Not Reproduction …]

“Whereas instructivists emphasize the transmission of standardized interpretations of the world by teachers and the educational communications they employ, as well as standardized assessments to test the degree to which students’ understandings match the accepted interpretations, constructivists are more interested in creating learning environments wherein learners use cognitive tools to help themselves construct their own knowledge representations. Cognitive tools and the goals, tasks, culture, resources, and human collaboration integral to their use enable learners to engage in active, mindful, and purposeful interpretation and reflection. In traditional instruction, active refers to stimulus, response, feedback, and reinforcement conditions that help students mirror accepted views of reality, whereas in constructivist learning environments, active learners participate and interact with the surrounding environment to create their own interpretations of reality.” (p 695)

[24.3.2 Designers as Learners …]

[24.3.3 Learners as Designers …]

[24.3.4 Experiential and Reflective Thinking …]

“Norman [1983] contends that computers support reflective thinking when they enable users to compose new knowledge by adding new representations, modifying old ones, and comparing the two.” (p 696)

[24.3.5 The Effects of Learning _with_ and _of_ Technology …]

[24.3.6 Meaningful versus Easy Learning …]

“When using cognitive tools, learners engage in knowledge construction rather than knowledge reproduction.” (p 697)

“Cognitive tools actively engage learners in creating knowledge that reflects their comprehension and conceptualization of information and ideas rather than absorbing predetermined presentations of objective knowledge. … Cognitive tools are not designed to reduce information processing, that is, make a task easier, as has been the goal of instructional design as a field and many previous instructional innovations. … Rather, cognitive tools are essential components of a learning environment in which learners are required to think harder about the subject-matter domain being studied or the task being undertaken and to generate thoughts that would be impossible without these tools. ” (p 697)

“… the enormous potential of cognitive tools can only be realized within a constructivist framework for learning.” (p 697)

[24.3. 7 (Un)intelligent Tools …]

“Cognitive tools, as we conceive them, are unintelligent tools, relying on the learner to provide the intelligence, not the computer. This means that planning, decision making, and self-regulation are the responsibility of the learner …” (p 697)

[24.3.8 Distributed Cognitive Processing …]

“The most pervasive cognitive technology is language. … Language amplifies the thinking of the learner.” (p 697)

[24.3.9 Summary of the Foundations for Cognitive Tools Research …]

“Cognitive tools will have their greatest effectiveness when they are applied within constructivist learning environments.” (p 698)

“Cognitive tools empower learners to design their own representations of knowledge rather than absorbing knowledge representations preconceived by others.” (p 698)

“Ideally, tasks or problems for the application of cognitive tools should be situated in realistic contexts, with results that are personally meaningful for learners” (p 698)

“Cognitive tools do not contain preconceived intelligence in the sense that intelligent tutoring systems are claimed to possess, but they do enable intellectual partnerships in the form o f distributed cognitive processing.” (p 698)


[24.5.1 What Are Computer Programming Languages? …]

[24.5.2 How Are Computer Programming Languages Used as Cognitive Tools? …]

“Computer programming is also dependent on various cognitive controls and styles of learners (Jonassen & Grabowski, 1993). Students who are field independent perform better in computer programming classes than field-dependent learners; i.e., field-independent students are more analytical thinkers.” (p 700)

“Chin and Zecker (1985) found that programming ability was not, as expected, related to math ability, but rather internal locus of control was a much better predictor. On the other hand, Nowaczyk (1983) found that mathematics and English course performance, previous computer experience, and logic and algebraic word problem performance were significantly correlated to programming performance among college students.” (p 700)

[24.5.3 What Learning Outcomes Result from Using Computer Programming Languages as Cognitive Tools? …]

“Harel (1991) maintains that one reason for the failure of LOGO skills to transfer to other domains is that teachers have often treated ‘LOGO as an object of knowledge in itself, rather than as a tool for acquiring other learning’ (p. 37).” (p 701)

“Why have the results of learning to program been so inconsistent and generally disappointing to the advocates of this approach? The answer may be found in both the nature of the cognitive tools themselves and the different approaches to applying them. Some cognitive tools such as databases, spreadsheets, and even hypermedia/multimedia authoring systems described later in this chapter share a common set of attributes (Jonassen, 1996). They are readily available, generic applications; they are affordable; they are used to represent knowledge in content domains; they are applicable across different subject domains; they engage critical thinking in learners; they facilitate transfer of learning; they are simple, powerful formalisms; and they are reasonably easy to learn.” (p 702)

“When cognitive tools become objects of study in and of themselves, as seems to be the case in many studies of the effects of programming, they cannot be expected to have major effects on higher-order thinking skills. However, where these tools are applied to meaningful and personally rewarding tasks, they may have much more impressive results.” (p 702)


[24.6. l What Are Hypermedia and Multimedia? …]

“Multimedia presentations are engaging because they are multimodal. In other words, multimedia can stimulate more than one sense at a time, and in doing so may be more attention getting and attention holding.” (p 703)

“Another problem is a lack of orientation as to how much of the hypertext the user has accessed and how much remains to be revealed.” (p 703)

[24.6.2 How Are Hypermedia/Multimedia Authoring Systems Used as Cognitive Tools? …]

“We contend that students are likely to learn more by constructing hypermedia instructional materials than by studying hypermedia created by others.” (p 704)

“Carver, Lehrer, Connell, and Ericksen (1992) suggest some of the major thinking skills that learners need to use as designers:

  • Project Management Skills: Creating a timeline for the completion of the project; Allocating resources and time to different parts of the project; Assigning roles to team members
  • Research Skills: Determining the nature of the problem and how research should be organized; Posing thoughtful questions about structure, models, cases, values, and roles; Searching for information using text, electronic, and pictorial information sources; Developing new information with interviews, questionnaires, and other survey methods; Analyzing and interpreting all the information collected to identify and interpret patterns
  • Organization and Representation Skills: Deciding how to segment and sequence information to make it understandable; Deciding how information will be represented (text, pictures, movies, audio, etc.); Deciding how the information will be organized (hierarchy, sequence) and how it will be linked
  • Presentation Skills: Mapping the design onto the presentation and implementing the ideas in multimedia; Attracting and maintaining the interests of the intended audiences
  • Reflection Skills: Evaluating the program and the process used to create it; Revising the design of the program using feedback”

(p 704)

[24.6.3 What Research Supports the Use of Hypermedia/Multimedia Authoring Systems as Cognitive Tools? …]

“This is a highly motivating process because authorship results in ownership of the ideas in the presentation.” (p 705)


[24. 7.1 What Are Semantic Networks? …]

[24.7.2 How Are Semantic Networks Used as Cognitive Tools? …]

“Constructing computer-based semantic nets engages learners in (1) the reorganization of knowledge through the explicit description of concepts and their interrelationships; (2) deep processing of knowledge, which promotes better remembering, retrieval, and the ability to apply knowledge in new situations; (3) relating new concepts to existing concepts and ideas which improves understanding (Davis, 1990); and (4) spatial learning through the spatial representation of concepts within an area of study (Fisher, Faletti, Patterson, Lipson, Thornton & Spring, 1990).” (p 707)

[24.7.3 What Research Supports the Use of Semantic Networks as Cognitive Tools? …]

“An important research agenda in learning psychology focuses on the expert-novice distinction, comparing student knowledge representation with teacher or expert representations. Research has shown that during the process of learning, the learner’s knowledge structure begins to resemble the knowledge structures of the instructors, and the degree of similarity is a good predictor of classroom examination performance (Diekhoff, 1983; Shavelson, 1972, 1974; Thro, 1978).” (p 707-708)


[24.8. l What Are Expert Systems? …]

“_Intelligence_ is the capacity to learn, reason, and understand.” (p 708)

[24.8.2 How Are Expert Systems Used as Cognitive Tools? …]

“When expert systems are used as cognitive tools, the roles of teachers and students change dramatically. Students as knowledge engineers assume a more active role in acquiring prerequisite knowledge and focusing and directing interactions with the teacher, who assumes the role of expert (Morrelli, 1990).” (p 709)


“So the use of spreadsheets as cognitive tools remains speculative.” (p 713)

[24.11.1 Future Research with Cognitive Tools …]

“The cognitive processes engaged by cognitive tools are complex and cannot be adequately assessed using a single type of measuring device. We recommend assessing the products of using cognitive tools as evidence of the thinking engaged by them.” (p 714)

“… research has shown that during the process of learning, the learner’s knowledge structure increasingly resembles the knowledge structures of the instructors, and the degree of similarity is a good predictor of classroom examination performance (Diekhoff, 1983; Shavelson, 1974; Thro, 1978).” (p 714)

Selected References

  • Carver, S. M., Lehrer, R., Connell, T. & Ericksen, J. (1992). Learning by hypermedia design: issues of assessment and implementation. Educational Psychologist 27(3), 385-404.
  • Chin, J. P. & Zecker, S. G. (1985). Personality and cognitive factors influencing computer programming performance. Paper presented at the Annual Meeting of the Eastern Educational Research Association, Boston, MA (ERIC Document No. ED 261666).
  • Davis, N. T. (1990). Using concept mapping to assist prospective elementary teachers in making meaning. Journal of Science Teacher Education 1(4),66-69.
  • Diekhoff, G. M. (1983). Relationship judgments in the evaluation of structural understanding. Journal of Educational Psychology 75, 227-33.
  • Duffy, T. M. & Jonassen, D. R., eds. (1992). Constructivism and the technology of instruction: a conversation. Hillsdale, NJ: Erlbaum.
  • Fischer, K. M., Faletti, J., Patterson, H., Thornton, R., Lipson, J. & Spring, C. (1990). Computer assisted concept mapping. Journal of College Science Teaching 19 (6), 347-52.
  • Harel, I., ed. (1991). Children designers: interdisciplinary constructions for learning and knowing mathematics in a computer-rich school. Norwood, NJ: Ablex.
  • Jonassen, D. H. & Grabowski, B. L. (1993). Handbook of individual differences, learning, and instruction. Hillsdale, NJ: Erlbaum.
  • Jonassen, D. H. (1996). Computers in the classroom: mindtools for critical thinking. Columbus, OH: Prentice Hall.
  • Morrelli, R. (1990). The student as knowledge engineer: a constructivist model for science education. Journal of Computing in Higher Education 2 (1), 78-102.
  • Norman, D. A. (1983). Some observations on mental models. In D. Gentner & A.L. Stevens, eds. Mental models. Hillsdale, NJ: Erlbaum.
  • Nowaczyk, R. H. (1983, Mar.). Cognitive skills needed in computer programming. Paper presented at the Annual Meeting of the Southeastern Psychological Association, Atlanta, GA (ERIC Document No. ED 236466).
  • Shavelson, R. J. (1974). Methods for examining representations of subject matter structure in students’ memory. Journal of Research in Science Teaching 11(3),231-49.
  • Shavelson, R. J. (1972). Some aspects of the correspondence between content structure and cognitive structure in physics instruction. Journal of Educational Psychology 63 (3), 225-34.
  • Stoll, C. (1995). Silicon snake oil: second thoughts on the information highway. New York: Doubleday.
  • Thro, M.P. (1978). Relationships between associative and content structure of physics concepts. Journal of Educational Psychology 70 (6), 971-78.


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