November/December 2001 // Commentary
Toward More Effective Instructional Uses of Technology: The Shift to Virtual Learning
by Michelle A. Johnston and Nancy Cooley
Note: This article was originally published in The Technology Source ( as: Michelle A. Johnston and Nancy Cooley "Toward More Effective Instructional Uses of Technology: The Shift to Virtual Learning" The Technology Source, November/December 2001. Available online at The article is reprinted here with permission of the publisher.

Educators are increasingly recognizing that technology is revolutionizing our field. Shank (2000), for example, argues that technology is altering the structure of education by disregarding institutional walls and developing new ways to access information, solve problems, and collaborate. These developments are particularly advantageous for students, who can now contact experts located at a distance when conducting their research. For example, while writing a paper on economic development in South America, a New York University student searched the Internet to locate and contact an economist in Argentina by e-mail. The economist not only shared information with the student, but also critiqued his paper and requested that the student send him a copy for his archives. In this case, technology clearly extended education by facilitating the student's contact with an international expert and promoting a relationship between student and expert that was sustained throughout all stages of the production of knowledge.

Furthermore, according to Tapscott (1999), contemporary students reap the benefits of growing up using computer technology and digital media for education and recreation. Specifically, an increasing number of students prefer to learn actively by surfing for information, solving problems, and finding new applications instead of passively by absorbing information through their instructors. For instance, fifth graders in Minnesota asked a memories listserv for information on the cause of World War II. The students discovered that the answers they received varied according to the respondents' countries of origin. In another case, business majors at a regional technical college in The Netherlands use technology to create their own businesses within a project-based model rather than studying about businesses from books and lectures. Because technology has impacted their lives so profoundly, current students often exhibit levels of technological sophistication and learning preferences different from the technological capabilities and teaching preferences of their instructors in traditional classes (Johnston, 2000).

In a collaborative project with the Milken Exchange on Educational Technology (1999), the International Society for Technology in Education (ISTE) advises that technology is changing the educational environment regardless of whether educators are prepared for the shift to technology-infused instruction. Students, their parents, and employers demand that educators assist students in becoming technologically literate citizens who can access, analyze, and evaluate electronic information. In addition, they expect that educators will prepare students to effectively select and use technological applications such as Internet communications tools (e.g., e-mail, listservs, threaded discussions, PDF file transfer, and document attachments), personal productivity tools (e.g., Microsoft Office Suite), and technologies for rapid prototyping in the workplace, i.e., using computer-generated images to design a three-dimensional model for immediate production. In order to respond to this constellation of expectations, educators have had to determine the appropriate uses of technology by aligning pedagogical and technical standards and assisting learners in demonstrating their mastery of the course objectives related to those standards.

Making the shift to a virtual learning environment

With the infusion of technology, teaching and learning automatically begin the move to a virtual environment where technology becomes transparent and student participation becomes paramount. However, such a move is not instantaneous. Rather it occurs gradually as instructors develop their own technological expertise and find new ways of teaching. Valdez, McNabb, Foertsch, Anderson, Hawkes, and Raack (1999) describe three phases in the shift to virtual learning, phases that depict the development of students' and instructors' sophistication and expertise in implementing instructional technology:

1. Automation. At this phase, the teaching and learning experiences depend on the technology and software, which guide the students' practice of basic academic skills through the use of traditional, rote methods. Professional development for the automation phase focuses the instructor's learning on computer and software operating procedures. Likewise, students focus on the same procedural aspects of operating the software, so the technology has little impact on their understanding of the discipline while the computer and its software often function as electronic worksheets.

For example, an instructor used WebCT to structure her instructional practice, which remained traditional, whole-group instruction, rather than using technology to accommodate different learning styles or create alternative learning environments. For one class session, the instructor scanned a worksheet on mean, mode, and median as part of an in-class demonstration. The instructor distributed paper copies of the worksheet and projected it on a screen. Working in triads, her students computed the means, modes, and medians. At the end of the exercise, the instructor asked the students to share their answers to the items on the worksheet. After the group completed the worksheet, the class discussion shifted from discourse on the discipline to a focus on procedures, including how to access information and how to submit papers through WebCT?¢‚Ǩ‚Äùa shift from the instructional goals to the WebCT procedures.

2. Transition. The computer and its software provide a framework within which students and teachers solve problems, investigate issues, and create products. Students word process, use spreadsheets, conduct Internet research, and prepare electronic presentations in response to their instructors' directions. They also interact through electronic chats and other types of enhanced communication. In this phase, professional development is more extensive since the technology effects changes in both pedagogy and practice.

For example, an instructor in an applied science class used Web-based case studies to provide information for students working in groups. The students posed a variety of questions using the prepared software. Depending on the questions, the program directed the students to case-related information that they organized for problem-solving. When students believed that they had enough information, they wrote reports and submitted them through the application. Students also participated in online chats and bulletin boards, while the instructor monitored their progress electronically. In this example, technology and software supported the instructor?¢‚Ǩ‚Ñ¢s instructional goals and governed the activities of the students, but they also allowed students to take different paths in their search for solutions.

3. Data-driven virtual learning. Students use computers and high-performance technology to create new knowledge and engage in meaningful learning. The students participate in self-directed research and become co-learners and curriculum developers with their professors. Within this phase, students also self-evaluate and devise constructs by which their performances and products blur the lines between teaching, learning, and assessment. Extensive professional development is necessary to implement such instruction since instructors may have to change fundamental aspects of their work (Valdez et al., 1999). Selection of the appropriate technology has to answer the following questions: Will the technology enhance the students?¢‚Ǩ‚Ñ¢ learning? Will it meaningfully engage the students in constructing new knowledge? Consequently, as instructors progress through the phases of technology integration in a virtual learning environment, their professional development grows in complexity, and they become more constructivist in their approaches to teaching (Ravitz, Becker, & Wong, 2000).

For example, an instructor invites students to work with municipalities to study groundwater quality. Students work in teams and use personal digital devices, laptops, CD ROMS, spreadsheets, and presentation software to develop testing protocols, data collection schedules, reporting procedures, and evaluation techniques for each municipality and body of water. Working with students, the instructor establishes a quality control rubric and procedural oversight. Rather than only submitting their reports to the instructor, students submit written reports, develop Web-based kiosks for explaining their findings and recommendations, and give presentations to representatives of the municipalities. In this phase, the technology is integral to all aspects of constructing knowledge, specifically from idea generation to the communication of results, and students' active engagement is critical.

New instructional models

New technologies within virtual learning environments are forcing pedagogical shifts—shifts from the teachers controlling the teaching to the students controlling the learning (Johnston, 2000). Not all students or faculty members are comfortable with this shift in control, and some continue to prefer more traditional models. Yet technology allows the exploration of multiple learning paths and different learning preferences by both students and instructors. Examining and preparing for a movement toward student control of learning is a daunting challenge, requiring extensive preparation by both professors and students. However, as Haddad (1999) suggests, change is worth it because technology-based innovative teaching and learning strategies can both enhance cognition and improve instructional management. Supported by powerful technologies, students can become responsible managers of their instruction, and instructors can become facilitators and co-learners. Ultimately, assessment and learning tasks can become more performance-based (Tinzman, Rasmussen, and Foertsch, 1999).

Two instructional models that have promise in a virtual learning environment are project-based learning and student-led inquiry. In the first model, project-based learning, instructors select the project or problem, and in the second, the control shifts to students who construct their own research questions:

1. Project-based or problem-based learning, which originated in the sciences, has applications in all disciplines. In this model, students and their instructors examine complex problems and construct new knowledge to solve problems using real-life resources and high-performance technology.

2. Student-led inquiry or research asks students to construct significant questions and to design strategies for answering those questions, presenting their findings, and evaluating their products and processes. The processes tend to be authentic, requiring higher levels of cognition, and relate both to real life issues and themes across disciplines. For example, an ecology instructor who wanted to design authentic and real-life learning opportunities for the students formed a partnership with neighboring communities in a regional groundwater quality and pond study. The students designed studies which culminated in reports to the appropriate partnering community organizations. Because they reflected specific communities' needs and students' findings, the study designs, procedures, and reports were all different.

Both student-led inquiry and project-based learning provide methodologies for virtual learning environments in which students take charge of their learning while the instructor facilitates. Within these learning environments, technology and instructional models become intertwined and support constructivist principles.


Technology, whether or not we are ready for it, is changing the way we work. Contemporary students, who are more technologically savvy than those of the past, demand pedagogical change. Furthermore, the societal imperative, expressed by the expectations of their parents, communities, and their future employers, promotes that change by asking for a technologically astute citizenry. Educators at all levels, and particularly at the postsecondary level, have to examine the instructional environment, shifts resulting from technology, phases of technology integration, and models of instructional practices along a continuum. The continuum moves from the automation level of technology integration through a transition level to data-driven virtual learning, which supports new and emerging models of instruction.

Technology has already changed the educational environment in which we teach in ways that instructors must recognize and address. Expectations regarding the role of instructional technology will continue to grow as new technologies emerge. Concomitantly, new instructors will create and implement new pedagogical models that will better capture students' mastery of course objectives made possible by high-powered technology.


Haddad, W. (1999). TechKnowLogia: It is about knowledge and learning. Unpublished manuscript.

The Milken Exchange on Educational Technology and Peter D. Hart Research Associates (1999). Transforming learning through technology. Santa Monica, CA: Milken Family Foundation.

Ravitz, J., Becker, H., & Wong, Y. (2000). Constructivist compatible beliefs and practices among U.S. teachers (Rep. No. 4). Irvine: Center for Research on Information Technology and Services. Retrieved May 16, 2001, from

Shank, R. C. (January 2000). A vision of education in the 21st century. Technology Horizons in Education (T.H.E.) Journal, 27(6), 42-45.

Tapscott, D. (1999). Growing-up digital. New York: McGraw Hill Professional Publishing.

Tinzmann, M. B., Rasmussen, C., & Foertsch, M. (1999). Engaged and worthwhile learning. In Fine, C. (Ed.), Learning with technology: Participants' manual (pp. 5-18). Oak Brook, IL: North Central Regional Educational Laboratory.

Valdez, G., McNabb, M., Foertsch, M., Anderson, M., Hawkes, M., & Raack, L. (1999). Computer-based technology and learning: Evolving uses and expectations. Oak Brook, IL: North Central Regional Educational Laboratory.

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