You are here:

3 Dimensional Teaching: evaluation for next generation

, Acadia university, Canada ; , Quebec University in Montreal, Canada

Global Learn, in Penang, Malaysia ISBN 978-1-880094-79-2 Publisher: Association for the Advancement of Computing in Education (AACE)


One day all the multimedia course content … might be easy to read and use on a book-sized. Many students may have difficulty reading a text on the screen. So (we) need to begin experimenting … on our current tools, if we hope to take full advantage of that future when it arrives Charles Hannon, 2008. What is the best practice to evaluate cognitive and linguistic skills for screen reading? How can we provide strategies to link the use of ICT and the development of skills of next generation student? These questions will be discussed in order to see how can we measure and evaluate student skills. This paper reviews recent advancements in cognitively-based test development and validation, and suggests various ways practitioners can incorporate similar methods into their own work. The frame work of this paper is 3 dimensional teaching and active learning Rosenshine, 1986, cognitive models for reading difficulties Gorin and Embretson, 2006.


Abou Zahra, M. & Bari, M. (2010). 3 Dimensional Teaching: evaluation for next generation. In Z. Abas, I. Jung & J. Luca (Eds.), Proceedings of Global Learn Asia Pacific 2010--Global Conference on Learning and Technology (pp. 978-983). Penang, Malaysia: Association for the Advancement of Computing in Education (AACE). Retrieved February 21, 2019 from .

View References & Citations Map


  1. Bari, M. And Gagnon, M. (2005): « Modeling interactive multimedia productions», In Recent Research Developments in Learning Technologies (m-ICTE 2005), A. Méndez-Vilas, B. González-Pereira, J. Mesa González, J.A. Mesa González (eds.), ISBN 609-5994-5, Pub. Formatex, Spain, pp. 531-534.
  2. 15 Feb. (2009): Montana State University, Bozeman, Montana Clark, R.C., and R.E. Mayer. (2007): e-Learning and the Science of Instruction. 2nd edition. San Francisco: Pfeiffer.
  3. Charles Hannon (2008): “ E-Texts in the Classroom” EDUCAUSE Quarterly, vol. 31, no. 1 (January– March 2008), pp. 12 – 13
  4. Gorin, J.S., & Embretson, S.E. (2006): Item difficulty modeling of paragraph comprehension items. Applied Psychological Measurement, 30(5), 394-411.
  5. Graesser, A.C., McNamara, D., & Louwerse, M. (2003): What readers need to learn in order to process coherence relations in narrative and expository text. In A.P. Sweet& C.E. Snow (Eds.), Rethinking reading comprehension (pp. 82-98). New York: Guilford Press.
  6. Graesser, A.C., McNamara, D., Louwerse, M. & Cai, Z. (2004): Coh-Metrix: Analysis of text on cohesion and language. Behavioral Research, Methods, Instruments and Computers, 36, 193-202.
  7. Jonassen, D. (2000): Computers as mindtools for schools. Columbus, OH: Merrill.-982 DASHDASH
  8. Leelawong, K, & Biswas, G. (2008): Designing Learning by Teaching Agents: The Betty's Brain System, International Journal of Artificial Intelligence in Education, Volume 18, Number 3 / 2008, pp 181-208
  9. Schiaffino, S., Garcia, P., Amandi, A. (2008): eTeacher: Providing personalized assistance to e-learning students, Computers& Education, Volume 51, Issue 4, December 2008, Pages 1744-1754
  10. Petersen, S.E. & Ostendorf, M. (2006): A machine learning approach to reading level assessment. University of Washington CSE Technical Report. Zimmerman, L., and A. Trekles Milligan (2007): “ Perspectives on Communicating with the Net Generation” , Innovate, , Retrieved, April, 2010.

These references have been extracted automatically and may have some errors. If you see a mistake in the references above, please contact