Bruce C. Howard

Metacognition and Self-Regulated Learning Constructs.

Demographic variables, findings from the Metacognitive Awareness Inventory (Schraw & Dennison, 1994), the Learning Strategies Survey (Kardash & Amlund, 1991), and the Motivated Strategies for Learning Questionnaire (Pintrich, Smith, Garcia, & McKeachie, 1991), as well as accuracy ratings of test performance, were examined in 2 studies. Findings indicated convergence of self-report measures of metacognition, significant correlations between metacognition and academic monitoring, negative correlations between self-reported metacognition and accuracy ratings, and positive correlations between metacognition and strategy use and metacognition and motivation. Limitations of the studies and implications for theory development and future research are discussed.

The Experience of Constructivism: Transforming Teacher Epistemology

Abstract The NASA Classroom of the FutureTM sponsored a residential training course to help teachers learn to use computer-based educational tools and explore constructivist instructional approaches. We hypothesized that creating a living-and-learning environment for the training would foster rapid changes in teachers’ epistemological beliefs. Pretest—posttest differences on an epistemology inventory indicated that teachers changed significantly on three of four factors related to constructivist teaching philosophies (Simple Knowledge, Quick Learning, and Certain Knowledge). The fourth factor (Fixed Ability) did not reveal significant changes. These findings have two implications: (1) constructivist approaches to training teachers may promote epistemological change, and (2) epistemology may be a less stable trait than was previously supposed.

The Influence of Metacognitive Skills on Learners' Memory of Information in a Hypermedia Environment

Twenty-eight students (aged 9 to 17) freely explored a science Web site structured either in an outline (linear) format or “puzzle” (non-linear) format for 2.5 hours. Subjects then engaged in tasks involving locational memory and informational recall. The results indicate that presence of metacognitive skills was a necessary but not sufficient condition for learning in hypermedia environments; the navigational structure of the Web site also was important. Metacognitive skill (as measured by the Junior Metacognitive Awareness Inventory (Jr. MAI) (Sperling, Howard, Miller, & Murphy, 2002) and the How I Study Questionnaire (HISP) (Fortunato, Hecht, Tittle, & Alvarez, 1991) was not a significant predictor of measures of retention within an outline structure (where the conventional structure did not stimulate meta-cognitive knowledge), while metacognition was a significant predictor of informational recall within the puzzle structure (which required active meta-cognitive knowledge to make meaning within the unfamiliar structure). The results point to the need for instructional designers to consider the structure of Web sites, with particular emphasis on the use of recognizable conventions, in order to reduce the metacognitive demands upon working memory involved in deciphering the structure.

The triarchic theory of intelligence and computer-based inquiry learning

Sternbergs (1985) triarchic theory of human intelligence distinguished among three types of intellectual abilities: analytic, creative, and practical. Our study explored the relationships between student abilities and the cognitive and attitudinal outcomes that resulted from student immersion in a computer-based inquiry environment. In particular, we examined outcome variables related to content understanding, problem solving, and science-related attitudes.Results indicated that more practical abilities predicted greater content understanding and transfer of problem-solving skills. High analytic abilities were predictive of content understanding but not transfer of problem-solving skills. High creative abilities predicted problem solving, but were not predictive of performance on content understanding. In terms of science-related attitudes, students who were dominant in practical abilities had significantly more positive posttest attitudes than those dominant in analytic abilities. The results from this study were used to make recommendations regarding design principles used in the subsequent development of computer-based inquiry environments.

Common Features and Design Principles Found in Exemplary Educational Technologies

As part of a larger project for the NASA-sponsored Classroom of the Futureâ„¢ to benchmark the effectiveness of educational technologies, researchers used multiple data sources to develop a list of exemplars and delineate common design features. The exemplars included promising educational technologies, tools, Web sites, resources, software, and hardware. Each exemplar was placed into one of six categories: knowledge and comprehension tools, interactive technologies and problem-solving tools, product-creation tools, efficiency and productivity tools, communication and collaboration tools, and technology tutors. The features of each exemplar were described, and a set of common design principles for that category was developed.

Evaluating Educational Technologies: A Historical Context

Our team of researchers reviewed published results from the last 15 years to compile a list of the characteristics of effective educational uses of technology. All the studies considered technical, administrative, and learning features, while more recent investigations emphasized administrative characteristics necessary to support No Child Left Behind reporting. Recommended characteristics have been similar over time with great concern that the technologies integrate into the curriculum and support professional development. The wide range of identified characteristics suggests that there is great hope that educational technology will solve many problems. Additionally, we provide a timeline of relevant historical milestones in the evaluation of educational technologies.

The Classroom of the Future and Emerging Educational Technologies: Introduction to the Special Issue

When discussing emerging educational technologies, the complaint around the globe is common enough: we may be outfitting schools with classrooms of the future, but teaching methods remain mired in the past. In this special issue of the International Journal of Information and Communication Technology Education, fresh perspectives for choosing and applying emerging educational technologies are presented as a result of the efforts of this investigation. Many well-respected experts have addressed the need for new methodologies. Instead, we have chosen to focus on the process of choosing the technologies themselves. We set out to determine how to evaluate the individual promise an educational technology may hold and to provide guidelines to those who choose and use the technologies for teaching and learning.

Design Principles for 21st-Century Educational Technology: Connecting Theory and Practice

Design principles are universal and may be translated onto the newest trends and emergent technologies. In this research study we combined the perspectives provided by two sources to create a set of recommended design principles for technology-enhanced learning environments. One source was the How People Learn framework (Bransford, Brown, & Cocking, 2000). The second source was a series of interviews conducted with pacesetters in the field of educational technologies. With the knowledge gained from these two sources, we created our own set of design principles. These principles can guide the evaluation of how educational technologies are used or help instructional designers in creating exemplary ways to implement technologies.

Emphasis on Educational Technologies Within National Science Foundation Projects

Our research team evaluated 18 months of National Science Foundation (NSF) program announcements and awarded programs to discern the amount and type of emphasis placed upon educational technologies. NSF issued 65 solicitations for proposals, with 53.8% calling for educational technology components. A sampling of 366 of the 1,180 funded projects showed that 34.7% included educational technology. Twenty-five percent of the projects were in biology and cognitive science, with another 40% in general science, computer science, technical education, engineering, and math. Many types of educational technologies were funded, with an emphasis on cognitive tutors/intelligent agents, distance learning, and online communities.

Conclusion and Next Steps: The EdTech Collaborative

In this special issue of the International Journal of Information and Communication Technology Education, we report on the results of a multifaceted research study on how to benchmark and use emerging educational technologies. Our approach blended classic research methods with those used in market research studies. We gathered data and expertise from a variety of sources, including academic research articles, industry reports, interviews with leaders and national pacesetters, and the experiences of our own veteran staff. Our objective was to create a means by which decisions about affordances, constraints, and effective use could be made in a just-in-time fashion. We have only scratched the surface.