Emerging applications of computer-based technology at all levels of education as well as continuing advances in learning theory present challenges and opportunities for assessment and pedagogy. Assessment and certification practices based on dated models of learning generally focus on outcomes without regard to processes and often fail to capitalize on the flexibility and power of computer-based technologies.
As computer-based technologies are applied in new ways to teaching and learning in K–12 schools, to higher education, and for professional training, they alter pedagogy as well as the types of skills and knowledge that learners develop. As a result, the impact that technology has on teaching and learning can often be difficult to measure using traditional assessment methods. The Journal of Technology, Learning, and Assessment (JTLA) is a scholarly, peer-reviewed on-line journal that provides an interdisciplinary forum where initiatives that combine technology, learning theory, and assessment are shared. The JTLA aims to help the learning community:
- Understand how technology can be applied to enhance learning;
- Explore the potential for computer-based technologies to enrich
- Apply new approaches to assessment utilizing computer-based technology;
- Reflect on applications of computer-based technology to learning
By advancing the development of new methods, tools, and approaches that apply technology to learning and assessment, the JTLA offers emergent perspectives and views for researchers, assessment and test developers, cognitive scientists, educational technology developers, teachers, school leaders, policy makers and test users. The JTLA encourages the publication of articles that take advantage of the capabilities of on-line publishing such as the use of multiple forms of media, inclusion of data sets to facilitate secondary analysis, links to relevant web resources, and relevant software applications.
Transparency in Research
The JTLA promotes transparency in research and encourages authors to make research as open, understandable, and clearly replicable as possible while making the research process – including data collection, coding, and analysis – plainly visible to all readers.