February 2001 — Features

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Assessing the Impact of Instructional Technology on Student Achievement

by Lorraine Sherry, Shelley Billig, Daniel Jesse, and Deborah Watson-Acosta

The significant correlations between motivation, metacognition, inquiry learning, and the student learning process score indicate that motivation may drive increases in the four elements connected by the first path. Similarly, the significant correlations between motivation, metacognition, application of skills, and the student product score indicate that motivation may drive increases in the four elements connected by the second path.

Based on the significant correlations of the two teacher measurements of student achievement with the student survey data, these data validated the evaluation team's extension of the Developing Expertise model to explain increases in student performance as a result of engaging in technology-supported learning activities. Moreover, nearly all students across the project met the standards for both the teacher-created student product assessment and the learning process assessment. This indicates that, in general, the project had a positive impact on student achievement.

 

X@XOpenTag002Conclusions

X@XCloseTag002These preliminary findings suggest that teachers should emphasize the use of metacognitive skills, application of skills, and inquiry learning as they infuse technology into their respective academic content areas. Moreover, these activities are directly in line with the Vermont Reasoning and Problem Solving Standards, and with similar standards in other states. The ISTE/NETS standards for assessment and evaluation also suggest that teachers:

  • Apply technology in assessing student learning of subject matter using a variety of assessment techniques.
  • Use technology resources to collect and analyze data, interpret results, and communicate findings to improve instructional practice and maximize student learning.
  • Apply multiple evaluation methods to determine students' appropriate use of technology resources for learning, communication and productivity.

 

Rockman (1998) suggests that "A clear assessment strategy that g'es beyond standardized tests enables school leaders, policymakers, and the community to understand the impact of technology on teaching and learning." RMC Research Corporation's extension of the Sternberg model can be used to organize and interpret a variety of student self-perceptions, teacher observations of student learning processes, and teacher-scored student products. It captures the overlapping kinds of expertise that students developed throughout their technology-related activities.

One of the greatest challenges facing the Technology Innovation Challenge Grants and the Preparing Tomorrow's Teachers To Use Technology (PT3) grants is to make a link between educational technology innovations, promising practices for teaching and learning with technology, and increases in student achievement. We believe that this model may be replicable in other educational institutions, including schools, districts, institutions of higher learning, and grant-funded initiatives. However, to use this model, participating teachers must be able to clearly identify the standards they are addressing in their instruction, articulate the specific knowledge and skills that are to be fostered by using technology, carefully observe student behavior in creating and refining their work, and create and benchmark rubrics that they intend to use to evaluate student work.