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  1. 1. AbstractIntroduction In a time when mobile devices such as smart phones and digital media players areubiquitous accessories of college students, it stands to reason that these devices are an avenuedown which educational information could be delivered at the undergraduate level. Severalstudies indicate that the use of supplementary aids, such as podcasts, provide learners withalternative access to lectures, notes, and summaries of curricular information. With the incorporation of mobile learning into many undergraduate classrooms, studentsare realizing benefits of an expanded classroom and access to an abundance of resources. Mobilelearning, or m-learning, provides the traditional student with opportunities for anytime learningthrough the use of everyday devices, such as cell phones, netbooks, and laptops (REF).Instruments for m-learning in this research proposal will be provided to the experimental groupand the course professor via a restricted access web-enabled smart phone to facilitate samplingthat does not require the personal economic means to own one. The students in the experimentalgroup and the professor use the provided iPhone smart phones to facilitate the delivery of onlinematerials that is available only to the experimental group. The purpose of this research proposal is to address the effects of m-learning tools onstudents in classes which incorporate m-learning as part of the curriculum, a learning trend that isforecasted to expand. The research question to be considered in this proposal is, "Does m-learning in undergraduate education affect academic achievement?"
  2. 2. Literature Review M-learning is defined by McConatha, Praul, and Lynch as “learning that is accomplishedwith the use of small, portable computing devices” (2008). As e-learning enables learningoutside of a classroom, m-learning enables learning irrespective of location (Wang, Wu, &Wang, 2009). It is a relatively new tool in the pedagogical arsenal that provides the traditionalstudent with opportunities for learning anytime through the use of everyday devices such as cellphones, netbooks, and laptops. Researcher Brian Alexander views the term m-learning as onethat often incorrectly implies wireless capabilities in conjunction with mobile technology (2004).In addition to the portability and efficiency, Alexander notes that the perceived privacy of mobiletechnology is a clear advantage. Mobile technology allows research to reach a new dimension inwhich collaboration is not limited to the lab. It is able to extend into the field with increased easeenabling collaboration outside of the local community to partners throughout the world for bothsharing and feedback (Alexander, 2004). With the incorporation of m-learning into manyundergraduate classrooms through both teaching and research, students are able to realize thebenefits of an expanded classroom and receive access to an abundance of resources. Fozdar and Kumar discuss m-learning as an effective tool for enhancing the teaching-learning process (2007). The study measures students’ attitudes and perceptions on theeffectiveness of m-learning. After a pilot test of 25 students, the authors conducted a 33 itemquestionnaire using a Likert scale to determine the perceived effectiveness of mLearning. Therewere 32 female and 33 males who responded for a 65% response rate, and though the samplesize is relatively small, the results of their study clearly indicate that m-learning can be aneffective way of learning. Zurity and Nussbaum research the supplementation of mobiletechnological resources specifically within constructivist learning environments (2004). Findings
  3. 3. confirm that m-learning can be applied in constructivist settings with positive impacts on studentlearning. While the study was developed based on face-to-face student interaction, theseresearchers successfully transferred the key principles of “constructive, active, significant,reflexive, collaborative and based on consultation” to the handheld technology setting.Educational content was not merely provided as a complement to direct instruction, but m-learning was successfully utilized as the key component in the creation of authentic studentwork, extending knowledge based upon peers’ contributed work via the handheld devices (2004).Student access to immediate feedback when using the m-learning devices may stand as acontributing factor in the resulting increased post-test scores. It has been proposed that digital audio in particular is an inexpensive and easy way toproduce elements that are successful in affecting attention, motivation, and interest (Chan & Lee,2005). Podcasts, delivered via downloadable files from the internet, is one format that enables astudent to choose content and view it when desired, potentially creating listening time that wouldotherwise be spent doing automatic tasks such as walking home or riding on the bus. Evans(2008) suggests that “podcasting can fill an important needs gap by allowing learners to continuelearning activities when it might not normally be possible.” This offers students more controlover their learning process and provides the learner with an active relationship with the classmaterial, ultimately constructing their own understanding of it. Material is delivered to studentsthrough a push method, allowing the ease of acquisition to become a tangible benefit andensuring that it is an “efficient, effective, engaging, and easily received learning tool forrevision” (2008). Evans and others intended to measure m-learning but did not controltechnology to ensure strictly mobile access to content. In fact, over 80% of the participants inEvans’ experiment were discovered to have chosen personal computers to access the material, a
  4. 4. device that does not meet the portability guidelines of most m-learning definitions (2008).McKinney, Dyck, and Luber (2009) use the same podcast technology but ensure m-learningcontent delivery through iTunes University, a website with downloadable educational podcasts.This study utilizes podcasts to deliver content in lieu of obtaining the notes from a missed lectureas opposed to previous studies that examined material designed to enhance a lecture. The resultsare generously in favor of podcasts for this particular use, with 88% of the experimental groupindicating future preference for podcasts over borrowed class notes in the event of a missedclass. Students in the experimental group performed significantly higher on exams and took moredetailed notes. Students appeared to value the ability to stop, rewind, and pause at will as well asthe opportunity to listen to the podcasts at any time of day. Since the majority of research in this area showcases positive relationships between theimplementation of m-learning and student learning experiences, Jie Chi Yang and Yi Lung Lin(2010) use this information to hypothesize positive effects on student-to-student informationsharing and collaborative learning through handheld mobile devices. By utilizing a shareddisplay groupware, Yang and Lin (2010) create an effective means for students to shareinformation and work with a group while maintaining the original information when using thehandheld devices. With the implementation of shared display groupware, users are not only ableto apply the handheld devices for course task completion, but to effectively facilitate groupdiscussion and sharing as well. The quality of material was not sacrificed due to small screensize and students were still able to work collaboratively, seamlessly employing the technology.The small screen size is one of the many factors that play into effort expectancy, a construct usedto measure belief of ease of utilization of m-learning and one of the five determinants of m-learning acceptance studied by Y. Wang, Wu, and H. Wang (2009). The research team also
  5. 5. studies performance expectancy (belief that an individual will attain job performance benefits),social influence (belief that important others view the individual as a m-learning user), perceivedplayfulness (level of cognitive spontaneity), and self-management of learning (belief in ability toengage in self-directed autonomous learning) with respect to age and gender to understand theacceptance of m-learning technology. They discover that each of the five categories is asignificant determinant of behavioral intention for both genders with the exception of socialinfluence for women. Additionally, all determinants were significant for both age categories (<30 and ≥ 30), but social influence and effort expectancy are stronger predictors of m-learningusage intention for the older group. This information is useful to targeting the audiences of m-learning with marketing techniques that are valuable for certain demographics and guidestechnology improvements that will aid the acceptance of m-learning throughout society. The rapidly changing and often complex technology found in the m-learning arena canmake it difficult for students to gain the skills and the knowledge through university curricula asquickly as needed in today’s world. In conjunction with industry, university technical services, aswell as various academic areas, Indiana University developed a graduate level course calledMobile Application Development to address this issue (Massey, Ramesh, & Khatri, 2006). Thecourse provided a way to immerse both students and faculty in the development of mobiletechnologies using problem based learning techniques with the dual goals of creating futuretechnical leaders in emerging mobile technologies and to expanding students’ knowledge basebeyond end users to developers and decision makers. Since many students today haveexpectations of conducting university coursework from anywhere and at any time, this coursebridged a gap from merely using the mobile technology for learning to actually developing thetechnology for future learners.
  6. 6. Much research on m-learning is completed in a higher educational setting with the goal ofenhancing student achievement or learning in some way. In a recent study completed by Chao-Hsiu Chen (2010), m-learning’s versatility is exhibited through a self and peer assessmentendeavor in a teacher education courses. This study demonstrates the use of PDAs to facilitateassessments in the classroom, thereby allowing students more opportunities for reflection ontheir own and others’ presentations. Using mobile devices for peer and self-assessments washypothesized to enhance students’ abilities to better evaluate performance standards, moreeffectively foster interaction, and better focus attention on in-class presentations. Because thestudents could easily both give and receive timely feedback more efficiently on the portabledevices, they were able to compare, reflect on, and improve on their presentation, which in turnled to improved subsequent performances.McConathaConclusion
  7. 7. ReferencesEvans, C. (2008). The effectiveness of m-learning in the form of podcast. ScienceDirect , 491-498.Chan, Anthony and Lee, Mark J.W. (2005) An MP3 a day keeps the worries away: Exploring theuse of podcasting to address preconceptions and alleviate pre-class anxiety amongstundergraduate. Good Practice in Practice. Proceedings of the Student Experience Conference 5-7th September ’05. Wagga Wagga, NSW: Charles Stuart University. Pp. 59–71.Chen, C. (2010). The implementation and evaluation of a mobile self- and peer-assessment system. Computers & Education, 55(1), 229-236. Retrieved from ERIC database.Massey, A., Ramesh, V., & Khatri, V. (2006). Design, development, and assessment of mobile applications: the case for problem-based learning. IEEE Transactions on Education, 49(2), 183-192. doi: 10.1016/j.compedu.2006.03.004.Alexander, B. (2004). Going Nomadic: Mobile Learning in Higher Education. EDUCAUSE Review, vol.39, no. 5 (September/October 2004): 28-35. Retrieved June 2, 2010 from, D., Praul, M., & Lynch, M. J. (2008). Mobile learning in higher education: An empirical assessment of a new educational tool. The Turkish Online Journal of Educational Technology, 7(3), 15-21.Zurita, G., & Nussbaum, M. (2004). A constructivist mobile learning environment supported bya wireless handheld network. Journal of Computer Assisted Learning, 20(4), 235-243.doi:10.1111/j.1365-2729.2004.00089.x.
  8. 8. Yang, J., & Lin, Y. (2010). Development and Evaluation of an Interactive Mobile LearningEnvironment with Shared Display Groupware. Educational Technology & Society, 13(1), 195-207. Retrieved from ERIC database.McKinney, D., Dyck, J. L., & Luber, E. S. (2009). iTunes university and the classroom: Can podcasts replace professors? Computers & Education, 52(3), 617-623.Wang, Y., We, M., & Wang, H. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92-118.Mobile Learning and Student Retention.