Onjira and Gilbert (2009) illustrate the affordances of machine-processable competency modeling. They argue that machine processing is invaluable in e-learning and assessment. They emphasize its effectiveness in e-learning. In addition, Onjira and Gilbert (2009) present the competency model’s affordances in generating questions, distractors, and adaptive query sequences. In the article, they conclude that using machine-processable competency overcomes many limitations in interoperability, reusability, and portability.
They illustrate that printing of non-English characters, deploying computers in language classrooms and developing language software are now possible because of advanced technology. The article by Fischer elaborated the role of technology in language learning. Smith and Schulze (2013) discuss replication while highlighting its benefits and possible causes of misunderstanding. They argue that not all studies can be replicated, but the existence of replication connotes maturity of the field.
Rabuzzi illustrates that dismissal state of STEM (science, technology, engineering, math) education is reported every week in the U.S. according to him, the risks in STEM subjects are because of the post-Cold War economic competition (Rabuzzi, 2014). Rabuzzi argues that improving STEM performance will foster talents of citizens as well as retain their world standing. He also argues that erasing the false divide that exists between scientific inquiry as well as humanistic learning will boost science education.
Hughes, J. (2013). Descriptive Indicators of Future Teachers’ Technology Integration in the PK- 12 Classroom: Trends from a Laptop-Infused Teacher Education Program. J. Educational Computing Research, 48(4) 491-516.
Hughes claims that integration of mobile technologies with professional teacher preparation will advance learning from one discipline approach to integrated learning approach. In connection with this claim, Hughes ...Show more