The effects of multitasking on learning in technology enhanced learning environments

Digital native, Net generation and millennium generation terms have been quite popular in the recent literature while describing the young generations. All these terms were grounded on the premise that the youth interact with digital technologies more than the previous generations. Some scholars claim that their excessive interaction with the technology changes their basic ways of learning, specifically in accessing the information and processing it in the mind. A common argument about the learning habits of digital natives is that they can split their attention between several information and communication resources, and can process the incoming information from a variety of those sources simultaneously. Referred to as multitasking, this notion is regarded as one of the most significant indicators of digital nativity. On the other hand, a rebuttal movement against both digital nativeness and their multitasking skills has been prominent in the recent literature. According to this view, human cognitive architecture is not capable of multitasking. Hence, individuals' performance outcomes and learning can be interfered significantly in multitasking situations. In this regard, the purpose of this study was to investigate the effects of multitasking on learning in technology enhanced learning environments. To realize this aim, a web-based learning environment was created which facilitated both learning and multitasking of students. The web environment sheltered sequential and disruptive, sequential and productive and concurrent and disruptive multitasking behaviors. In the sequential and disruptive multitasking environment, participants switched between two tabs at certain times on their computer screen. One of these tabs contained an instructional video and the other one contained funny or interesting video clips. In the sequential and productive multitasking environment, both tabs contained two different instructional videos, and participants could switch between them at certain points. In both sequential multitasking environments, instructional videos were paused when participants passed to the other tab, and resumed from the paused moment when they switched back to the previous tab. On the other hand, in concurrent and disruptive multitasking environment, participants were presented only one tab and were not allowed to pause instructional video when multitasking. In the concurrent multitasking environment, participants did online chatting as the multitasking activity during learning. Two instructional videos were presented to the students in the aforementioned multitasking environments. These videos were about the life cycle of malaria and the renewable energy resources. The study was realized through a quantitative research methodology. There were two control and five experimental groups in the true-experimental factorial design of the study. The experimental groups did one of the three aforementioned multitasking activities while learning from video content, whereas control groups watched these videos without multitasking. All participants were assigned to their treatment group randomly. The participants of the study were 572 pre-service teachers studying at the Faculty of Education at Anadolu University, Turkey. Participants in all treatment groups were compared in terms of two learning performance indicators. The cognitive gains of students from the video content were measured with a retention test while the affective outcomes were measured with a topic interest scale. Comparison of the retention test scores with the control groups revealed no significant loss in disruptive or productive sequential multitasking situations. However, a significant loss in the retention scores was observed in the concurrent multitasking situations. It was also observed that the topic interest scores across the multitasking situations varied according to the instructional video presented to the participants. Among the groups who watched the life cycle of malaria, the topic interest scores in sequential multitasking situations was similar to the control group, whereas it was significantly worse than the control group in the concurrent multitasking situations. None of the groups who watched the renewable energy resources video were significantly different from the control group in terms of topic interest. However, the topic interest stayed steady for the sequential and disruptive and concurrent and disruptive groups from pretest to posttest. A significant increase was observed in sequential and productive groups only. In addition to the comparison of students' learning performances in different multitasking situations, the relationship between their multitasking skills and several personal characteristics were investigated in the study as well. These features were digital device experience, daily time spent in various digital media platforms, frequency of multitasking while studying, and working memory capacity. The analysis did not reveal a significant relationship between digital device ownership and multitasking skills. Similarly, no relationship was observed between daily time spent on digital media and multitasking in sequential and disruptive and concurrent and disruptive multitasking situations. On the other hand, a negative correlation was identified between the daily time spent on digital media and multitasking skill in sequential and productive multitasking situations. Considering that the total instructional video duration was two times longer in sequential and productive multitasking situation, it can be claimed that spending longer times in digital media has negative effects on longer learning activities. Another significant contribution of this study is that it addressed whether the skill of multitasking in learning environments can be improved by doing multitasking while studying. Indeed, statistical analysis addressed no relationship between frequency of multitasking in the study environments and the posttest retention scores. Finally, the current study avers that the learning success in different multitasking situations might be related to different working memory constructs of the mind. In the current dissertation, the findings summarized above were discussed thoroughly in light of the relevant literature. The discussion was followed by the limitations of the study and suggestions for further research. The manuscript ends with the discussion of the theoretical contributions of the study to the multitasking framework, and addressing the practical applications of the current findings to the design of learning activities in digital environments. Key words: Digital natives, multitasking, web-based learning