Academic journal article T H E Journal (Technological Horizons In Education)

Predictors of Performance in the Virtual Classroom: Identifying and Helping At-Risk Cyber-Students

Academic journal article T H E Journal (Technological Horizons In Education)

Predictors of Performance in the Virtual Classroom: Identifying and Helping At-Risk Cyber-Students

Article excerpt

The ability of instructors to identify at-risk cyber-students quickly is critical because the usual cues associated with student anxiety, inattentiveness or apathy are not present in the virtual classroom. For instance, cues such as frowning, fidgeting and daydreaming, which are often readily apparent in the conventional classroom, are not observable by Web-based instructors. Due to the lack of these traditional cues, cyber-instructors must develop other strategies for identifying at-risk students in the virtual classroom. In addition, conventional solutions, such as office hours and graduate teaching assistants, for assisting low-performing students are not typically available in Web-based classes. Therefore, cyber-instructors must be creative in devising strategies for helping their at-risk students. We describe several strategies whereby cyber-instructors can take advantage of the technologically rich learning environment of the Internet in helping their students. Effective use of these strategies can also help reduce attrition rates in Web-based courses.

Web-Based Instruction

We have taught three different Web-based psychology classes. In the past five years we have taught more than 30 online sections and, in any given semester, we typically teach concurrent conventional and online sections of a class. Students freely choose to register for the class format they desire. We use the same course syllabus, textbook, homework assignments and examinations to facilitate comparisons across these two learning formats. The equivalence of course materials across class formats is purposeful. Our approach to online instruction has always been one in which pedagogy rather than technology guides the design of our Web-based classes. Therefore, we have attempted to find ways to use Internet technology to re-create important pedagogical aspects of our conventional classes in the Web-based format.

Many of our course materials are available on the course home page. This means that prospective students can obtain information about the course content, such as the syllabus, grading policy and calendar, as well as our approach to online instruction before deciding to register for the course. Further, the home page has links to Web sites that describe characteristics of successful cyber-students. These links allow prospective students to evaluate their own learner characteristics and technological proficiencies regarding Web-based courses. For instance, the distance learning link found at offers students a short online survey that evaluates their readiness for an online course. Our home page also encourages prospective students to contact us before registration if they have any concerns or questions about the content and technological demands inherent to the online course.

In our online class, delivery of course materials and instructor-student interactions occur via both asynchronous and synchronous modes of communication. Asynchronous modes include e-mail, fax, forum (discussion) postings and downloadable information from the Web site. Synchronous communication occurs primarily in our 90-minute online lectures using a chat room, which are scheduled on a weekly basis. In this article we will describe several predictors of cyber-student performance. If instructors are vigilant, these predictors can serve as early warning indicators for student failure as well as success in the virtual classroom.

Demographic and Educational Predictors

It may come as a surprise, but basic demographic characteristics such as gender and age are not reliable predictors of cyber-student performance (Wang and Newlin 2000). While there may be a perception that male teen-agers might have a technological advantage, research does not show systematic differences in performance as a function of gender and age for the college population. Indeed, we are not aware of any research demonstrating that there are reliable demographic predictors of performance among college students who choose to take online courses. …

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