Social Media for Learning and Teaching Undergraduate Sciences: Good Practice Guidelines from Intervention pp431‑441
Abstract: In 2013, Facebook was used in learning and teaching clinical problem solving in a Pathology and a Clinical Sciences course delivered at a South Australian university. It involved first‑ and second‑year Medical Radiation students and second‑year Nursing students, Of the 152 students enrolled in the Pathology course, there were 148 students who participated in the Facebook group. Of the 148 students, 61 (41%) completed the invited post‑intervention questionnaire. At the same time, all 17 nursin g students enrolled in a science course at the regional campus of the same university participated in the Facebook initiative, however, only 10 (59%) completed the post‑intervention questionnaire. A good practice and checklist were developed from the p ost‑intervention evaluations, which consisted of 25 Likert‑ and open‑type questions. Both student cohorts found the use of Facebook beneficial for them in terms of providing an innovative way of learning; fostering greater interaction amongst co‑students and staff; and effectively engaging them with the content of courses. The importance of clear communication of goals and objectives to students was identified from student comments. Six good practice principles were identified relating to: goals and objec tives, expectations, communication, engagement with the course content, active participation, and learning environment.
Keywords: Keywords: Facebook, social media, medical radiation, nursing, guidelines for good practice, engagement
Synthesizing Technology Adoption and Learners Approaches Towards Active Learning in Higher Education pp442‑451
Abstract: In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners variations, particularly regarding their styles and a pproaches to learning, on intention and use of learning technologies. This study contributes to further examine a working model for learning outcomes in higher education with the Unified Theory of Acceptance and Use of Technology (UTAUT) on SRS adoption attitude, and the Study Process Questionnaire (SPQ) on students approach to learning. Adopting a cross‑section observational design, the current study featured an online survey incorporating items UTAUT and SPQ. The survey was administered to 1627 und ergraduate students at a large comprehensive university in Hong Kong. Relationships between SRS adoption attitude, learning approaches, and learning outcomes in higher‑order thinking & learning and collaborative learning were analyzed with a structural eq uation model (SEM). A total of 3 latent factors, including four factors from UTAUT in Performance Expectancy, Effort Expectancy, and Deep Learning Approach from the SPQ, were identified in the structural model on students intention to adopt SRS in clas ses. Current results suggested that a model of active learning outcomes comprising both UTAUT constructs and deep learning approach. Model presented in the present study supported the UTAUT in predicting both behavioral intention and in adopting SRS in la rge classes of undergraduate education. Specifically, positive attitudes towards SRS use measured with the UTAUT, via a learning approach towards deep learning, accounted for variation on high‑impact learning including higher‑order thinking and collaborat ive learning. Results demonstrated that the process of technology adoption should be conceptualized in conjunction with learners diversity for explaining variation in adoption of technologies in the higher education context.
Keywords: Keywords: Technology adoption, Learning Approaches, Students Response System, SRS, Higher Education
Abstract: Courses in virtual learning environments can leave recently enrolled participants in a state of loneliness, confusion and boredom. . What course content is essential in the course, where can more information be found and which assignments are ma ndatory? Research has stated that learner control and motivation are crucial issues for successful online education. This paper presents and discusses visualisation as a channel to improve learners control and understanding of programming concepts and ga mification as a way to increase study motivation in virtual learning environments. Data has been collected by evaluation questionnaires and group discussions in two courses partly given in the Moodle virtual learning environment. One course is on Game bas ed learning for Bachelors programmes, the other is a course on e‑learning for university teachers. Both the courses have used progress bars to visualise students study paths and digital badges for gamification. Results have also been discussed with teac hers and pedagogues at a department for computer and systems sciences. Furthermore, two visualisation prototypes have been designed, developed and evaluated in programming lectures. Findings indicate that visualisation by progress bars is a good way to im prove course participants overview in online environments with rich and multifaceted content. To what degree the visualisation facilitates the course completion is hard to estimate, and like students have different learning styles, they also seem to have different visualisation needs. Gamification by digital badges seems to have various motivational impacts in different study groups and in traditional university programmes the traditional grades seem to be the main carrots. Finally, it seems that softwar e visualisation might be a promising path to enhance programming education in the 21st century.
Keywords: Keywords: Visualisation, Gamification, Programming education, Virtual learning environments, E-learning
Online Continuing Education for Health Professionals: Does Sticky Design Promote Practice‑relevance? pp466‑474
Abstract: Online continuing education (CE) holds promise as an effective method for rapid dissemination of emerging evidence‑based practices in health care. Yet, the field of CE continues to develop and delivery is predominately face‑to‑face programs. P ractice‑oriented online educational methods and e‑learning platforms are not fully utilized. Educational theorists suggest an experiential approach to CE consistent with adult learning theory. A compelling question remains: Can online asynchronous CE prog ramming prepare health care providers in delivering higher‑level practice competencies?. To address this question, the authors have identified seven composite ⠜sticky⠀ factors that have been critical to the engagement of learners and the creation and delivery of practice‑oriented online educational programs (Zaghab et al, 2015). The sticky factors are based in knowledge management (Nonaka, 1994; Szulanski, 2002) and adult education or andragogy (Knowles, 1970; 1984). In this paper, sticky factor s are mapped to Moore and colleagues⠒ (2009) higher level learning outcomes in health care CE. Data are presented on learner reported practice‑related outcomes in a selection of online CE courses on the CIPS Knowledge Enterprise⌢ portal with the Uni versity of Maryland School of Pharmacy⠒s Center for Innovative Pharmacy Solutions (CIPS). A dynamic, adaptive e‑learning environment built by technology partner, Connect for Education, Inc., provides the innovative platform and the Acclaim! interactiv e learning technology. This technology‑instructional partnership is dedicated to an iterative continuous improvement process called the Learner Stewardship Cycle (Zaghab et al, 2015). The cycle improves stickiness and learner engagement in order to achi eve higher‑level learning outcomes in CE. Findings suggest that of the 769 learners successfully completing an online course with two or more sticky design segments, the majority report reaching level 4, 5 and 6 learning competencies. Learners from the pr ofessions of pharmacy, nursing, medicine, and other health
Keywords: Keywords: Health Care Practitioner, continuing education, situated online learning, learner engagement, continuous improvement, and practitioner-learner