Higher Education Success Factors: A Literature Review

I completed this literature review for my supervisor. I applied research methodologies to not only enhance my own practice but to help solve issues with students dropping out of online programs.

Higher Education Success Factors – Word Document

A Literature Review: Online Higher Education / Online Teacher Education Success Factors

Databases used in this review were Google Scholar and Boise State University’s Albertsons Library EBSCOhost. Search terms included: Online Teacher Education Program Success Factors, Online Education Success Factors, Online Higher Education, Online Teacher Education, Teacher Education Program Online, Online Graduate Program Success, Graduate Student Success Factors in Online Teacher Education Programs, Graduate Student Success in Online Programs, Online Teacher Professional Development Success Factors, Online Teacher Education Case Study, Online Teacher Education Success and Failure Factors and Identifying Online At-Risk Graduate Students. Articles were excluded if they were not available in fulltext, they did not contain new information, or if they did not contain specific factors contributing to success or failure in online higher education or online teacher education. The search was limited by the time frame of 2008-present and all related articles on the first five pages of the search were included.

Factors identified as either predicting success or failure can be categorized into the following levels: Administrative, Instructor, Course, and Student.

At the administrative level, factors that contribute to the success of an online program consist of; supplying adequate technological support for teachers (Baran & Correia, 2014; Cain Phillip, Ting, Gonzalez, Johnson, & Galy, 2013;  Crawford-Ferre & Wiest, 2012; Harrell, 2008), up-to-date technological devices, and proper professional development opportunities (Cain et al., 2013), while providing pedagogical support (Baran & Correia, 2014) and access to a relevant community of practice (Cain et al., 2013; Baran & Correia, 2014; Baran, Correia, & Thompson, 2011). Reducing the teaching load on instructors or allowing use of a teacher’s aid are other ways to improve success rates of an online program at the administrative level (Cain et al., 2013).

At the level of instructor, factors contributing to the success of an online program consist of providing students with abundant involvement including: quality interactions, support, feedback, and evaluations (Hart, 2012; Cain et al., 2013; Crawford-Ferre & Wiest, 2012; Lee & Choi, 2011; Macfadyen & Dawson, 2010), supplying a well structured and designed course (Lee & Choi, 2011; Cain et al., 2013; Baran & Correia, 2014; Hart, 2012; Crawford-Ferre & Wiest, 2012), and developing an online pedagogy different from that of a traditional face-to-face classroom (Baran et al., 2011).

At the course level, factors recommended for a successful online program include an online orientation for students (Harrell, 2008; Crawford-Ferre & Wiest, 2012), a frequently asked question page, and a resource page. Course assignments should include specific expectations and instructions, as well as adequate context and abundant audio/visual aids (Crawford-Ferre & Wiest, 2012). Multiple forms of content exploration both synchronous and asynchronous should be available for various student learning styles (Crawford-Ferre & Wiest, 2012; Harrell, 2008; Terrell, Snyder, & Dringus, 2009; Perry, Boman, Care, Edwards, & Park, 2008). Course communications are recommended to be plentiful and varied utilizing both synchronous and asynchronous methods (Crawford-Ferre & Wiest, 2012; Cain et al., 2013; Falloon, 2011, Terrell et al., 2009), and provide formal and informal options for student interaction (Crawford-Ferre & Wiest, 2012; Terrell et al., 2009).

At the student level, factors found to contribute to success in an online program are time management skills (Hart, 2012; Cain et al., 2013; Dray, Lowenthal, Miszkiewicz, Ruiz‐Primo, & Marczynski, 2011), self efficacy, a positive locus of control (Hart, 2012; Dray et al., 2011; Lee & Choi, 2011; Harrell, 2008), and support from peers (Hart, 2012; Lee & Choi, 2011; Cain et al., 2013; Terrell et al., 2009). Other student factors that were found to impede on success are learning style (Hart, 2012; Harrell, 2008; Perry et al., 2008), lack of basic computer skills (Hart, 2012; Lee & Choi, 2011; Dray et al., 2011; Harrell, 2008), limited access to resources or technology (Hart, 2012; Dray et al., 2011), a lower overall GPA (Lee & Choi, 2011; Harrell, 2008), and less academic and/or professional experience (Lee & Choi, 2011). The critical student factor for failure in an online program was a feeling of isolation (Hart, 2012; Cain et al., 2013; Crawford-Ferre & Wiest, 2012, Falloon, 2011; Terrell et al., 2008). Multiple forms of communication and instructor presence are recommended for students feeling isolated including adequate amounts of student to student interactions as well as student to instructor and student to content (Crawford-Ferre & Wiest, 2012; Falloon, 2011; Terrell et al., 2008; Harrell, 2008).

A review of administrative, instructor, course and student factors contributing to the success of online programs can assist in predicting students at-risk for failure enrolled in online programs. Multiple studies attempt to identify these students using data from pre-enrollment surveys gauging student readiness (Dray et al., 2011; Harrell, 2008), to a connectedness scale developed to determine the amount of isolation a student is feeling (Terrell et al., 2008). The most effective method reviewed is an analysis of LMS tracking data following the amount of student to student interactions via discussion boards, student to instructor interactions via a mail component, and student to content interactions via self assessment attempts. The latter of the three predicting with 81 percent accuracy students that received a failing grade although tracking data must be customized to reflect the pedagogical intent of the course under study (Macfadyen & Dawson , 2010).

 

An, Heejung, Sangkyung Kim, and Bosung Kim. “Teacher perspectives on online collaborative learning: Factors perceived as facilitating and impeding successful online group work.” Contemporary issues in technology and Teacher Education 8.1 (2008): 65-83.

A study analyzing data collected from 24 students of a virtual graduate school of education program on factors that affect online group work. Data was collected via an open ended online survey and analyzed using a quantified qualitative method.  Factors identified as facilitating successful group work include: individual accountability, affective team support, the presence of a positive group leader, consensus building skills, and clear instructions. Factors identified as impeding successful group work include: lack of individual accountability, challenges inherent to virtual communication relying solely on written language, technology problems, unclear instructional guidelines, different time zones, lack of a positive leader, and lack of consensus building skills. While individual accountability was considered to be a critical factor in both successful and unsuccessful group work, the perceived importance of affective team support leaves the authors asking, “ Is affective team support a more critical factor when the course is held in an online environment?”.

 

Baran, E., & Correia, A. (2014). A professional development framework for online teaching. TechTrends, 58(5), 95-101.

A professional development framework for online teaching, developed from previous research and literature, emphasising the support from teacher, community, and organizational levels necessary for successful online teaching in higher education. An in depth analysis of how to support online teachers at each level is given: at the teaching level emphasis is put on technological, pedagogical and design support, at the community level communities of practice and peer support are emphasised, and at the organization level a strong organizational culture is necessary for a successful online program.  Along with support from each level, factors identified as contributing to the success of online courses include: time invested on planning and organization, efforts put into managing courses, increased teaching presence, and increased social presence.

 

Baran, E., Correia, A., & Thompson, A. (2011). Transforming online teaching practice: critical analysis of the literature on the roles and competencies of online teachers. Distance Education, 32(3), 421-439.

A literature review, analysis, and synthesis on the topic of online teachers’ roles and competencies revealing that for an online program to be successful, not only do the roles of teachers need to adapt to online environments but also teacher pedagogies. The authors put emphasis on the reason for failure of online courses being the replication of traditional roles and competencies from face-to-face to online environments and “onesize-fits-all

preparation and support programs for online teachers”. The review ends with a suggestion for teacher preparation and development programs to encourage a collaborative culture of online teachers practicing critical reflection, pedological inquiry, and problem solving in order to create their own online teacher personas, and in turn, successful online courses.

 

Cain, M., Phillip, S., Ting, S. R., Gonzalez, L. M., Johnson, J., Galy, E., et al. (2013). An Exploration of Students’ Experiences of Learning in an Online Primary Teacher Education Program. Journal of Online Learning & Teaching, 9(3).

A study examining the experience of eight students in an online undergraduate education program offered through The University of the West Indies. Although they had to take three prerequisite courses online to familiarize themselves with the format, all eight students, as well as the supporting faculty, were new to online courses. The study revealed that while students choose to take online classes due to convenience and flexibility, there were other factors that contributed to their success such as personal attributes: commitment, planning, and time management, peer support: collaboration, peer tutoring, and emotional support, support form other sources: Open Campus site personnel, and site technicians, online tools: forums, YouTube videos, WebQuests, chats, and wikis, teleconferences: real-time interaction and feedback, and course materials: course design and layout. Factors found to impeded on the success of the students were lack of time management, inadequate instructions, feelings of isolation, lack of feedback, too many course activities, lack of face-to-face instruction, and technological challenges. Overall it was found that for an online course to be successful students must be self-driven and organized and the course must include adequate amounts of collaboration and instruction.

 

Crawford-Ferre, H. G., & Wiest, L. R. (2012). Effective online instruction in higher education. The Quarterly Review of Distance Education, 13(1), 11-14.

A literature review and summary of effective practices in online pedagogy revolving around three categories: new methods of course design, interaction among course participants, and instructor preparation and support. In the category of course design, the review suggests the following for implementation of successful online instruction: compatible technology supporting international formats, technology support for teachers and students, an online orientation of the LMS for students, a frequently asked questions and helpful resources page, multiple methods of content exploration (both synchronous and asynchronous), and multiple options for communication including formal (structured) and informal (unstructured) settings. Following are suggestions in the category of interaction among course participants: abundant collaboration/communication opportunities between students (both asynchronous and synchronous), substantial instructor involvement, adequate content and context for assignments, specific information about expectations, and greater use of audio/visual aids.

In the last category, instructor preparation and support, the authors suggest: proper professional development, training, or preparation specific to online teaching and technology, access to proper technology and technical support, reduced teaching load or the use of a teacher’s aid, and access to a community of practice for additional support.

“More research is needed on how to prepare and support online instructors. Research should also be conducted on student experiences, motivators for participation, and perceptions of relative strengths and weaknesses of various aspects of online education”

 

Dray, B. J., Lowenthal, P. R., Miszkiewicz, M. J., Ruiz‐Primo, M. A., & Marczynski, K. (2011). Developing an instrument to assess student readiness for online learning: A validation study. Distance Education, 32(1), 29-47.

An article reviewing the development of a survey that assess whether or not a student will do well in an online class based on personal characteristics and technology capabilities. The survey was created using three phases: develop and review, item analysis, statistical analysis of reliability and validity. The personal characteristics that were indicative of a successful online student are individual beliefs in their ability to complete a college degree, beliefs about responsibility in problem solving (academic and technical), self-efficacy in writing and expression, orientation to time and time management, and behavior regulation for goal attainment. The technology capabilities portion of the survey measures basic technology skills such as the ability to use email and the Internet, as well as material access to technology, such as devices and bandwidth, and the nature and frequency of technology use. The survey seems valid and reliable though the article does not list specific characteristics or technology capabilities that predict a successful online student.

 

Falloon, G. (2011). Making the connection: Moore’s theory of transactional distance and its relevance to the use of a virtual classroom in postgraduate online teacher education. Journal of Research on Technology in Education, 43(3), 187-209.

A study analyzing the effect of a synchronous virtual classroom on student satisfaction. The study uses the lens of Moore’s theory of transactional distance when observing student satisfaction. Moore’s theory has three factors which are dialogue: any form of interaction that is of high quality and is efficient in solving student problems, structure: the level of the course’s rigidity or flexibility including clear instructions and objectives, and learner autonomy: the students’ sense of independence in the course. The third factor is contingent on the first two as a lack of structure or dialogue can increase a students dependence on the instructor. The study announces that a critical factor of student failure in online courses is their feeling of isolation due to lack of the three factors. The goal of the study was to observe the effect of a synchronous virtual classroom on students experience with this feeling of isolation. The study revealed that dialogue improved but structure declined due to students lack of flexibility, therefore learner autonomy decreased as the students were more dependent on the virtual class meeting times. In conclusion, a successful online course will offer optional synchronous virtual classroom meetings for students needed extra support in the dialogue category.

 

 

Harrell, I. L. (2008). Increasing the Success of Online Students. Inquiry, 13(1), 36-44.

An article outlining three broad categories that increase success of online students; student readiness, student orientation, and student support. To improve retention rates of online programs it is recommended that institutions employ a readiness survey to gage student attributes as they relate to success in online courses such as learning style, locus of control, computer skills, and self-efficacy. Following a student’s GPA, the existence of an online orientation was the second greatest factor in predicting online success. Technical and personal around the clock support is another factor in predicting student success.

 

Hart, C. (2012). Factors associated with student persistence in an online program of study: a review of the literature. Journal of Interactive Online Learning, 11(1), 19-42.

A literature review focused on factors contributing to student persistence and/or success in an online program. Factors identified include: flexibility, asynchronous format, time management, goal commitment, quality of interactions and feedback, satisfaction and relevance, self-efficacy and personal growth, social connectedness or presence, and support from peers. Factors identified as impeding on success are: learning style, basic computer skills, difficulty in accessing resources, isolation and decreased engagement, lack of computer accessibility, non-academic issues, and poor communication. This is an in depth literature review close to our topic of interest.

 

Lee, Y., & Choi, J. (2011). A review of online course dropout research: implications for practice and future research. Educational Technology Research and Development, 59(5), 593-618.

A literature review and analysis identifying 44 factors that contribute to student dropout of online courses. These 44 factors were organized into three categories: student factors, course/program factors, and environmental factors each with subcategories.  The first category, student factors, has four subcategories, academic background: lower GPA equates to higher dropout rate, relevant experience: more academic or professional experience equates to lower dropout rate, relevant skills: higher management skills meant lower dropout rate and lower computer skills ment higher dropout rate, and psychological attributes: positive attitudes toward school, the course, instructor, other students, locus of control, motivation and self efficacy meant lower dropout rates. The second category, course/program factors, has three subcategories, course design: well structured and relevant equated to lower dropout rates, institutional supports: lack of administrative structure, evaluation, and student support equated to higher dropout rates, and interactions: higher teacher-student interactions meant lower dropout rates as with higher student-content, but surprisingly student-student had no effect.  The last category has two subcategories, work commitments: more work commitments increased dropout rate,  and supportive study environments: higher amounts of emotional support from family and friends resulted in lower dropout rates as with a comfortable place to study and financial aid. This is a great study for our topic as it addresses factors contributing to failure unlike most other studies which focus on success factors.

 

Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588-599.

An analysis of LMS tracking data to identify at risk students according to their engagement with the online course. The study is looking a student-student, student-faculty, and student-content interactions identifying three predicting factors; number of forum postings, mail messages sent, and assessments completed. The model accurately predicted 81% of students to receive a failing grade. measures of total time spent online correlate only weakly with student final grade. visualizations of student tracking data for a selected course must be highly customizable to reflect pedagogical intent.

 

Perry, B., Boman, J., Care, W. D., Edwards, M., & Park, C. (2008). Why Do Students Withdraw from Online Graduate Nursing and Health Studies Education?. Journal of Educators Online, 5(1), n1.

A qualitative study reporting students’ self proclaimed reasons for withdrawing from an online nursing program. Reasons are categorized into two sections personal reasons: life circumstances and work commitments, and program reasons: learning style and evolving career aspirations.

 

Terrell, S. R., Snyder, M. M., & Dringus, L. P. (2009). The development, validation, and application of the Doctoral Student Connectedness Scale. The Internet and Higher Education, 12(2), 112-116.

An application study of the Doctoral Student Connectedness Scale, a scale developed to identify at risk doctoral students on the grounds of connectedness. It was found higher feelings of student-student and student-faculty connectedness resulted in less attrition.

 

 

 

 

 

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AECT Poster Proposal

 

AECT Poster Proposal– Word Document

 

Sarah Baughman
Boise State University

Educational Technology

sarahbaughman@u.boisestate.edu

(208)755-9384

 

Title: Usability Evaluation of an Online Video Feedback Software Within an American Sign Language Context

 

Short Description –

A poster presentation outlining an evaluation of the contextual video feedback tool: GoReact. The presenter reports findings on the usability, efficiency, effectiveness, and impact of the tool when providing contextual feedback on student created videos demonstrating American Sign Language acquisition. Information presented is especially useful to attendees employing the use of student created videos to demonstrate knowledge but is also applicable to those looking for a creative way to make and use instructional videos.

 

Session type: Poster

Category of Session: Research Proposal

AECT Divisions, Councils and National Affiliated Organizations: Emerging Learning Technologies (usability testing, evaluation of instructional multimedia)

Key Words:

Video Assessment, distance education, technology integration

 

Abstract:

 

Educational Context

An American Sign Language (ASL) department at a mid sized northwest university will begin employing the use of GoReact, a contextual video feedback tool, with two courses in the Spring 2016 semester. The usability, efficiency, effectiveness, and impact of the tool will be evaluated and results presented in this poster session. Information presented on this tool is of great interest to any teacher or instructor that employs the use of student created videos to demonstrate knowledge and performance, long-distance or face-to-face. The evaluation will focus on the use of this tool for providing effective and timely feedback but it should be noted here that there are many creative applications of this emerging technology that can reach a wide range of teachers and subjects.

 

Background

The recent increase in online video has sparked many studies on its use and impact in education (Artz, Bernstein, & Arithi, 2013; Cleary & Bates, 2014; Moonaghi et al, 2012; Tuong, Larsen, & Armstrong, 2014; Tsur & Beck, 2014). The use of video in the classroom is thought by many to have a major impact on education (Harvey, 2015), but this impact has not yet been felt due to factors, including but not limited to, video assignments lacking the functionality to provide students with immediate and effective feedback (Foertsch et al., 2002, McKinney & Page, 2009 and O’Bannon et al., 2011). The ever pressing issue of collecting and providing feedback on instructional and student created videos has drawn attention to the lack of video assessment software available to teachers. This issue can be especially pressing in American Sign Language classrooms as the nature of the language tends to require use of multiple student created video assignments. One common method of assessing student created videos is to have students upload their video to YouTube where teachers review and grade it online, then provide written feedback separate from the video itself (Alpay & Gulati, 2010). Providing effective feedback is difficult enough (Crook, 2012),  while providing effective feedback on student created videos is nearly impossible. Trying to write out feedback on a rubric or in an email is lengthy and ineffective as students rarely go back and watch their video while reviewing written comments. This could be detrimental to the progression of student learning as the significance of effective feedback has been noted in multiple studies (Alpay & Gulati, 2010; Crook, 2012; Stigler, Geller, & Givvin, 2015). One emerging technology, GoReact, has been developed to alleviate this feedback issue. However, few formal evaluations on its effectiveness have been done.

 

GoReact is a cloud-based software that allows teachers and students the ability to upload and share videos. Instructors are able to access student videos and provide immediate contextual feedback into the video via audio, video, or written comments. GoReact saves all uploaded videos, is easily linked with an LMS, provides an integrated rubric and grading system, and keeps track of group analytics. This makes it easy for teachers to see how often students review their feedback all the while tracking student progress toward performance outcomes. GoReact can not only be used to provide feedback but can also be used to create instructional videos by uploading a video and adding teacher comments or questions. It can then be the location of a streaming lecture where students have a real-time discussion in a chat style side panel. Although GoReact  provides many features, this evaluation will focus merely on its effectiveness as a feedback tool in regards to student created videos.

 

Data Collection

The data collected for this evaluation will be designed to measure progress toward the following goals:

  • High student and teacher perceived ease of use (usability)
  • Reduced grading time for teachers (efficiency)
  • More effective feedback for students / decrease in repeat student error (effectiveness)
  • Increase in student language skill and confidence (Impact)

The data will be collected from four courses, two that are using GoReact and two that are not. Data will be collected through interviews with teachers and students, pre and post semester surveys, formative surveys throughout the semester, and analytics available through GoReact.

 

The presentation will include a poster summarizing evaluation results as well as an iPad available for a hands on learning experience with the tool. Attendees will be able to explore the tool and it’s capabilities while simultaneously reviewing common questions regarding employment of this new technology in their classrooms. The presenter will provide student and teacher perspectives on the usability of the software including time spent navigating and learning the software, time spent providing and reviewing feedback, positive and negative features of the software, perceived improvement in language skill and confidence, and overall satisfaction. Graphs to be included on the poster are as follows; a comparison of the amount of time teachers spend providing feedback with GoReact versus without, a comparison of the number of times students review feedback via GoReact versus re-watching their YouTube videos, and a display of the increase in student language skill and confidence with and without GoReact feedback.

 

Implications

This presentation will provide language teachers with a research driven evaluation of the video feedback tool GoReact. The evaluation will not only add to the body of knowledge on best practice video assessment but can also be used to determine if this tool, or another like it, can provide teachers with reduced grading time and more effective feedback to improve student learning and confidence with second language use. Not only language teachers will benefit from this information as any teacher that utilizes student created video can use this tool evaluation for more efficient and effective assessment.

 

Conclusion

With video becoming more popular as an instructional tool as well as an avenue for student demonstration of learning, an effective video assessment tool is a necessity. GoReact is one option and this evaluation will shed light on its usability, efficiency, effectiveness, and impact in the context of providing feedback on student created ASL videos.  

 

 

References

Alpay, E., & Gulati, S. (2010). Student-led podcasting for engineering education. European Journal of Engineering Education, 35(4), 415-427.

 

Artz, P., Bernstein, R., & Arithi, P. (2013, October). Streaming Media for Each Student in Every Class: Interdepartmental Best Practices for Accessible, Legal, Affordable, and Effective Video Delivery to Online Students. In World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (Vol. 2013, No. 1, pp. 575-580)

 

Cleary, C. E., & Bates, A. (2014). Online video in education: acquisition, value & ROI.

 

Crook, A., Mauchline, A., Maw, S., Lawson, C., Drinkwater, R., Lundqvist, K., … & Park, J. (2012). The use of video technology for providing feedback to students: Can it enhance the feedback experience for staff and students?.Computers & Education, 58(1), 386-396.

 

Foertsch, G.A. Moses, J.C. Strikwerda, M.J. Litzkow. (2002). Reversing the lecture/homework paradigm using eTeach® web-based streaming video software. Journal of Engineering Education, 91 (3) (2002), pp. 267–274

 

Kay, R. H. (2012). Exploring the use of video podcasts in education: A comprehensive review of the literature. Computers in Human Behavior,28(3), 820-831.

 

McKinney, K. Page. (2009). Podcasts and video streaming: Useful tools to facilitate learning of pathophysiology in under graduate nurse education?. Nurse Education in Practice, 9 (6) (2009), pp. 372–376 http://dx.doi.org.libproxy.boisestate.edu/10.1016/j.nepr.2008.11.003

 

Moonaghi, H. K., Hasanzadeh, F., Shamsoddini, S., Emamimoghadam, Z., & Ebrahimzadeh, S. (2012). A comparison of face to face and video-based education on attitude related to diet and fluids: Adherence in hemodialysis patients. Iranian journal of nursing and midwifery research, 17(5), 360.

 

O’Bannon, J.K. Lubke, J.L. Beard, V.G. Britt. (2011). Using podcasts to replace lecture: Effects on student achievement. Computers & Education, 57 (3) (2011), pp. 1885–1892

 

Stigler, J. W., Geller, E. H., & Givvin, K. B. (2015). Zaption: A Platform to Support Teaching, and Learning about Teaching, with Video. Journal of e-Learning and Knowledge Society, 11(2)

 

Tuong, W., Larsen, E. R., & Armstrong, A. W. (2014). Videos to influence: a systematic review of effectiveness of video-based education in modifying health behaviors. Journal of behavioral medicine, 37(2), 218-233.

 

Tsur, M., & Beck, J. (2015). The State Of Video in Education. Global Learn,2015(1), 201-203.