Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…

Strengths and weaknesses of prevailing evaluation models are analyzed, with attention to the role of feedback in each paradigm. A framework is then presented for analyzing issues faced by evaluators of interactive instructional technologies. The current practice of evaluation relies heavily on 3 models developed over 20 years ago: (1) the…

In order to "cut through the jargon of the multifaceted field of evaluative research", 21 evaluation models representing a range of possibilities were identified (via literature review) and compared in terms of purpose and five basic phases applicable to rural development. Evaluation was defined as "the systematic examination of a…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…