Predicting Preservice Science Teachers' TPACK through ICT usage

Designing effective and efficient learning environments by integrating recent educational technologies into the teaching process has become an important goal of education for nearly two decades. However, earlier studies showed that a higher level of technology knowledge does not guarantee the development of TPACK. At this point, studies guided by the transformative approach defining TPACK as a unique knowledge revealed encouraging results for a better understanding of technology-integrated instruction. This study aims to investigate to what extent ICT usage categories predict preservice science teachers' TPACK. Totally 326 preservice science teachers with a mean age of 21.62 (SD = 1.41) from seven different universities participated. For that purpose, a correlational study was conducted. The ICT-TPACK-Science Scale and the ICT Usage Questionnaire were used to collect data. Six separate multiple regression analyses were conducted to predict TPACK measures using ICT measures. Results indicated that approximately a third of the variability in total-TPACK scores can be accounted for by three ICT measures. The relative importance of individual predictors is arranged in the following order desktop software, emerging ICTs, and hardware. As for the dimensions of the ICT-TPACK-Science Scale, the overall effect of the ICT predictors decreased in the following order: Designing, implementing, planning, proficiency, and ethics. Emerging ICTs made the highest contribution to the designing and proficiency dimensions; while desktop software made the highest contribution to the implementing, planning, and ethics dimensions. To sum up, this study describes the association between ICT usage and TPACK in the view of the transformative ICT-TPACK-Science framework. The utilization and transformation of ICT tools as a cognitive partner for effective and efficient science teaching in different TPACK dimensions needs further investigation.

Learning anatomy via mobile augmented reality: Effects on achievement and cognitive load

Augmented reality (AR), a new generation of technology, has attracted the attention of educators in recent years. In this study, a MagicBook was developed for a neuroanatomy topic by using mobile augmented reality (mAR) technology. This technology integrates virtual learning objects into the real world and allow users to interact with the environment using mobile devices. The purpose of this study was to determine the effects of learning anatomy via mAR on medical students' academic achievement and cognitive load. The mixed method was applied in the study. The random sample consisted of 70 second-year undergraduate medical students: 34 in an experimental group and 36 in a control group. Academic achievement test and cognitive load scale were used as data collection tool. A one-way MANOVA test was used for analysis. The experimental group, which used mAR applications, reported higher achievement and lower cognitive load. The use of mAR applications in anatomy education contributed to the formation of an effective and productive learning environment. Student cognitive load decreased as abstract information became concrete in printed books via multimedia materials in mAR applications. Additionally, students were able to access the materials in the MagicBook anytime and anywhere they wanted. The mobile learning approach helped students learn better by exerting less cognitive effort. Moreover, the sensory experience and real time interaction with environment may provide learning satisfaction and enable students to structure their knowledge to complete the learning tasks. Anat Sci Educ 9: 411-421. © 2016 American Association of Anatomists.