UC Community Based Participation in Iran Research Paper

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This is a two paper work

1) Quantitative research

2) Qualitative research

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ISBN: 978-989-8533-63-0 © 2017 WHY DO LEARNERS CHOOSE ONLINE LEARNING: THE LEARNERS’ VOICES Hale Ilgaz and Yasemin Gulbahar Ankara University, Distance Education Center, 06830 Golbasi, Ankara, Turkey ABSTRACT Offering many advantages to adult learners, e-Learning is now being recognized - and preferred - by more and more people, resulting in an increased number of distance learners in recent years. Numerous research studies focus on learner preferences for online learning, with most converging around the individual characteristics and differences, if not the features of the technology and pedagogy used. For Turkey, the situation is also similar, with the number of adult learners who prefer online learning increasing each year due to several reasons. The result of this is an increase in the number of online programs offered by many universities. Hence, this research study has been conducted to reveal the prevailing factors causing learners to choose online learning. Through this qualitative research regarding online learners in a state university, it is found that having a full time job, accessibility and flexibility, individual responsibility, effective time management, physical distance, institutional prestige, disability are the common factors for under graduate and graduate learners in their preference for online learning. Awareness of these factors can support the stakeholders while designing e-Learning from both technological and pedagogical points of view. KEYWORDS Online learning, preferences, expectations 1. INTRODUCTION Offering many advantages to adult learners, e-Learning is now being recognized - and preferred - by more and more people, resulting in an increased number of distance learners in recent years. Emphasizing that distance education has a bright and promising future, Zawacki-Richter and Naidu (2016) stress that, “In fact, there has never been a better time to be in the field of open, flexible, distance and online education than now!” (p. 20). The commonly discussed factors that make online learning attractive for adults are: independence from time and place; accessibility, and; economic reasons. With the MOOC movement, extremely high quality online courses are now being delivered to learners by many well-known universities. Moreover, many universities are either providing online programs or courses as a support to traditional instruction, in the form of blended learning, flipped classes, etc. Indeed, there are almost no universities left who don’t benefit from these advantages of technology usage and its support in teaching-learning processes. A variety of reasons might account for these learning preferences. Çağlar and Turgut (2014) attempted to identify the effective factors for the e-learning preferences of university students; they concluded that, “Efficient usage of time and reduced educational expenses were found to be on top of the list as the most valued advantages of e-learning” (p. 46). Moreover, having responsibilities, a full-time job and no access to a nearby university may also cause learners to prefer online learning. Among the factors that affect learners’ attitudes toward e-learning, a positive attitude toward technology, ease of access and use of internet, computer literacy, perceived usefulness, self-efficacy, motivation, patience, self-discipline, and self-regulation seem to be widespread and the most commonly reported (Liaw, Huang & Chen, 2007; Nogueira & Machado, 2008; Sun, Tsai, Finger, Chen & Yeh, 2008; Bertea, 2009). On the other hand, Lim and Morris (2009) examined the influence of instructional and learner variables on learning outcomes for a blended instruction course and stated that “… age, prior experiences with distance learning opportunities, preference in delivery format, and average study time are those learner antecedents differentiating learning outcomes among groups of college students” (p. 282). 130 International Conference e-Learning 2017 Regardless of learners’ attitudes toward e-learning, instructional design plays an all important role during an efficient online learning process. From the literature, it can be seen that the most common instructional design models – such as ADDIE, ASSURE, Dick & Carrey, Smith & Ragan - start with the analysis step. This step can be broken down into analysis of the learner, content, media and aim. Nevertheless, the question is: after analysis, are designers really reflecting the possible applications in their instructional design process? In many online learning programs learner analysis was carried out collecting learners’ general demographic data. Even if the target group of learners have similar academic backgrounds, these learners tend to have very different individual properties (Navarro & Shoemaker, 2000; Conrad & Donaldson, 2010), expectations (Dabbagh, 2007; Moskal & Dziuban, 2001) and motivation (Keller & Suzuki, 2004; Kearsley, 2002) levels. Therefore, after enrollment, institutions or practitioners should conduct a deep learner analysis; this also influences the quality of instructional design in a holistic way. Thus, institutions can aim to decrease the drop-out rates (Park & Choi, 2009; Chyung, 2001), increase the attendance (Yudko, Hirokawa & Chi, 2008; Rovai, 2003) and, in general terms, maintain a more efficient learning process. Numerous research studies have focused on learner preferences for online learning, with most converging around the individual characteristics and differences, if not the features of the technology and pedagogy used. A similar situation is seen in Turkey, with the number of adult learners who prefer online learning increasing each year due to several reasons. The result of this is an increase in the number of online programs offered by many universities. For this reason, the current research study has been conducted to reveal the prevailing factors causing learners to choose online learning. Thus, this research seeks answers to the following research questions: 1. 2. What are the factors that affect students’ preferences for online learning? Are there any differences between program types in terms of student preferences? 2. METHODOLOGY 2.1 Research Design This research is designed as a qualitative study. Participants were requested to answer two online open-ended questions at the beginning of fall semester, and asked underlying reasons for their choice of online learning method, and their expectations about online learning. 2.2 Participants Participants of this study were the online learners of a state university who were enrolled in various e-learning programs. These programs were composed of six undergraduate degree and four graduate degree programs. Most of the online learners were females (55%), married (59%) and aged 18-25 (41%). Detailed demographics for the participants are presented in Table 1. Table 1. Participant demographic data Female Male Single Marital Status Married 18-25 26-33 34-41 Age 42-49 50 and up Total Gender Undergraduate f % 1278 59,92 855 40,08 1032 48,38 1101 51,62 29 9 136 41 112 34 45 14 7 2 2133 100 Graduate f % 184 55,93 145 44,07 133 40,43 196 59,57 860 41 761 36 398 19 80 4 18 1 329 100 131 ISBN: 978-989-8533-63-0 © 2017 2.3 Data Analysis After checking all of the responses, it was found that 944 participants from undergraduate level and 178 participants from graduate level were suitable for data analysis. The collected data was coded separately by the researchers. None of the qualitative data analysis software has been used, because of not missing any statement. In this research, coding was conducted according to the participants’ comments, and the codes and themes were generated by the researchers. A member checking validation strategy was used in this research for validity (Creswell, 2007), and also an intercoder agreement strategy was used for reliability. Two different coders - apart from the researchers analyzed the codes and themes for a second time. For this dataset, Cohen’s Kappa coefficient was calculated and found to be 0.90, which is within the range of acceptability (Krippendorff, 2004; Landis & Koch, 1977). In terms of member checking, researchers called (via phone) 10 randomly selected participants, and talked about their online learning experiences and reasons for their preferences. During meetings they emphasized the similar preferences for online learning. 3. RESULTS 3.1 Undergraduate Students After the qualitative analysis, researchers identified 12 themes within the undergraduate students’ data. The themes for undergraduate level are presented in Table 2. Table 2. Themes for undergraduate students Themes Having a full time job Accessibility and flexibility Individual responsibility Effective time management Individual difficulties Features of learning environment Physical distance Academic preference Having a second degree Institutional prestige Aging Disability Total f 441 218 113 106 83 82 43 23 16 10 8 8 1151 % 38,31 18,94 9,82 9,21 7,21 7,12 3,74 2,00 1,39 0,87 0,70 0,70 100 According to the data analysis, having a full time job is the most significant theme regarding the student’s reasons for their preferences. They stated that the desire to run their work life and education together, and also the high tempo of work life forcing them to choose distance education programs. The majority of students were between 26 and 41 years of age, this data also proves that these students can be active workers in life. The students stated their situation, as is seen in the example below: “I am working, and my age is 35. Still, I can complete my education into my area of interest, and have a diploma via distance education.” [P-722]. “I am working, and I don’t have any time for traditional learning programs. I choose this program, because it was the only way for me to learn.” [P-715]. 132 International Conference e-Learning 2017 The other emerging theme was that of accessibility and flexibility. The nature of distance education is that it is independent from location and time, which are also important criteria in terms of students’ preferences. “Distance education gives me a large choice of time and location, so I don’t need to be at an exact place and time. Also, I can continue to my other diploma program which I enrolled in before.” [P-23]. “It’s very easy to access and the practical, discretionary participation feature to the synchronized sessions is very important for me. Also, the opportunity of listening to sessions from records, and from different lecturers makes me choose distance education.” [P-92]. “I choose distance education, because I can study whenever I want. I can listen to session recordings and there isn’t an obligation about attending synchronized sessions.” [P-373]. Another characteristic of distance education students is that, generally, they couldn’t complete, or even start, their education because of their individual responsibilities. This situation can be seen from the codes and themes emerging from the data. Most of the students stated that they have to take care of their family and children, or even a relative such as a nephew, or their grandparents. “I had to choose distance education, because there is no one to take care of my nephew.” [P-53]. “I am married, and have 3 kids. I really appreciate that this opportunity is provided to us.” [P-491]. “I choose distance education because I am married and have 2 kids. My kids are going to elementary school, so they need me at home.” [P-592]. According to the analysis, a point will soon be reached where the large majority of students are likely to enroll on a distance education program, as this enables them to manage their time very efficiently, and also handle with family and work responsibilities as well. Financial problems and being in a prison are addressed in the individual difficulties theme. Students stated that living far away from the university can cause a high level of transportation, accommodation and educational expenses for them. As a solution to such potential financial issues, they prefer distance education. In addition to this, students who have been in prison stated that continuing their education through distance education is a huge disadvantage for them even if in their circumstances. After analyzing the students’ data, researchers found that students consider distance education as systematic, coordinated, repeatable, offering good interaction with teachers, enabling participation from home, creating the chance for individual work, containing visual-audio presentation techniques, and offering virtual classroom activities. All of these specifications are considered in the features of the learning environment theme. Physical distance, having a second degree, institutional prestige, aging and disability themes also emerged from the qualitative data. Students stated their reasons as follows: “I have a physical disability; as a result of this, transportation is a problem for me. So, I choose distance education” [P-522]. “I am a congenitally hearing disabled person; with distance education I can listen to my courses over and over” [P-840]. “The city I lived in doesn’t have my program’s formal version” [P-121]. “I am travelling a lot because of my job, so I have to be in different cities most of the time” [P-327]. “The appealing factor for me was the university’s prestige. Having a diploma from such big university is very important for me” [P-878]. “I lost the chance to go to university years ago. I believe that learning should be from birth to death. Now I am at the age of 35, and continuing my education at this age makes me happy” [P-911]. 133 ISBN: 978-989-8533-63-0 © 2017 3.2 Graduate Students After analyzing the graduate students’ data, 8 themes arose. Compared with the under graduate students’ themes, it was found that there were 7 common themes, and only 1 of these was different from the others. These themes are presented in Table 3. Table 3. Themes for graduate students Themes f % Having a full time job Effective time management Accessibility and flexibility Lifelong learning Physical distance Individual responsibility Institutional prestige Disability Total 90 42 26 24 13 7 1 1 204 44,12 20,59 12,75 11,76 6,37 3,43 0,49 0,49 100 The lifelong learning theme consisted of students’ wishes about increasing their academic knowledge, and providing professional development. Within the context of these aims, they stated that the reasons for their preferences as: “Distance education provides me with continuing education, and I’m improving myself academically as well as in my work life” [P-13]. “I believe in lifelong learning, but I am dealing with a high tempo work life. I couldn’t attend a traditional program because of my workload, so I choose distance education. Distance education is a very useful system for busy people like me” [P-46]. “I choose distance education because it was the most appropriate method with which I can continue with minimum loss elsewhere. Besides, I believe that, after completing this program, I will be in a better position in my work life” [P-53]. When looking over the order of the themes, having a full time job was the most important, as was the case in the undergraduate program students’ data. Effective time management, and accessibility and flexibility were the next themes in terms of importance. Also being married, having children, living outside of the city or country, and being a part of a leading university were the other reasons mentioned. 4. CONCLUSION The results of this study indicate the importance of distance education, which can provide the equality of opportunity independent of graduation level. Every person has the right to obtain a quality education, regardless of whether it is a graduate or undergraduate degree. Sometimes life obstacles can be a barrier in front of people’s choices. In this study, the researchers aimed that identify the differences between students’ reasons for their preferences for distance learning. It was found that, generally, these reasons were parallel between these two degrees, but also there were some differences regarding certain points. The common themes for both of the groups were having a full time job, accessibility and flexibility, individual responsibility, effective time management, physical distance, institutional prestige, and disability. The differences were in terms of preferences at graduate degree level, individual difficulties, features of the learning environment, academic preference, obtaining a second degree and the aging process. For graduate students, the predominant difference was the desire for lifelong learning. Actually, these themes tend to represent the students’ characteristics. Undergraduate degrees are fundamental for finding a job, so this is an obligation for most students. Because of this, people who have difficulties regarding their budget, health issues or special conditions prefer distance education to a greater extent. Similar difficulties aren’t observed at graduate level. Graduate level is not an obligation for a job; it depends much more on intrinsic motivation. 134 International Conference e-Learning 2017 This is why these seven themes weren’t evident in the data analysis. According to the analysis, people who enroll on a graduate level program are seeking more professional development. According to both qualitative and demographic data, those people who can’t complete or even start their education due to family responsibilities are, generally, the female students. Consequently, with distance education female students are able to find their place in social and work life much more effectively than before. Social roles and/or cultural expectations can bring about certain disadvantages to females, but it is shown that distance education can play an important role in overcoming these issues. Hence, although this research does not add any specific new findings to the field, it was important to revisit the underlying factors influencing learner preferences, since technology and pedagogy should be shaped according to these needs. Providing education services to all the people who need them, and also increasing the quality of education in an accessible way provides numerous benefits to people’s lives. With the use of regular tracking systems, educational practitioners can better understand students’ reasons for preferring distance learning, as well as their expectations. Thus, institutions can provide a more enhanced and comprehensive service. REFERENCES Bertea, P., 2009. Measuring students’ attitude towards e-learning: A case study. The 5th International Scientific Conference E-Learning and Software for Education. Bucharest, Romania. Retreieved at February 28, 2016 from https://adlunap.ro/else2009/papers/979.1.Bertea.pdf Conrad, R. M., & Donaldson, J. A., 2010. Engaging the Online Learner: Activities and Resources for Creative Instruction. Wiley, San Francisco, USA. Çağlar, E. S. & Turgut, T., 2014. Factors Effecting E-Learning Preference: An Analysis on Turkish University Students from Government and Private Institutions. Emerging Markets Journal, Vol. 4, No. 1, pp. 42-48. Chyung, S. Y., 2001. Systematic and systemic approaches to reducing attrition rates in online higher education, American Journal of Distance Education, Vol. 15, No.3, pp. 36-49. Creswell, J.W., 2007. Qualitative inquiry and research design: Choosing among five approaches (2nd ed.). Sage Publications, Thousand Oaks. CA, USA. Dabbagh, N., 2007. The online learner: Characteristics and pedagogical implications. Contemporary Issues in Technology and Teacher Education, Vol. 7, No. 3, pp. 217- 226. Kearsley, G., 2002. Is online learning for everybody? Educational Technology, Vol. 42, No. 1, pp. 41–44. John K. & Katsuaki S., 2004. Learner motivation and E-learning design: A multinationally validated process. Journal of Educational Media, Vol. 29, No. 3, pp. 229-239. Krippendorff, K., 2004. Content analysis: an introduction to its methodology (2nd ed.). Sage Publications, Thousand Oaks. CA, USA. Landis, J. R. & Koch, G. G., 1977. The Measurement of Observer Agreement for Categorical Data. Biometrics, Vol. 33, No. 1, pp. 159-174. Lee, Y. & Choi, J., 2011. A review of online course dropout research: implications for practice and future research. Educational Technology Research & Development. Vol. 59, No. 5, pp. 593-618. Liaw, S.S., Huang, H.M. & Chen, G.D., 2007. Surveying instructor and learner attitudes toward e-learning. Computers & Education. Vol. 49, No. 4, pp. 1066-1080. Lim, D. H., & Morris, M. L., 2009. Learner and Instructional Factors Influencing Learning Outcomes within a Blended Learning Environment. Educational Technology & Society, Vol. 12, No. 4, pp. 282–293. Moskal, P. D., & Dziuban, C. D., 2001. Present and future directions for assessing cybereducation: The changing research paradigm. Cybereducation: The future of long-distance learning. Mary Ann Liebert, New York, USA. Navarro, P., & Shoemaker, J., 2000. Performance and perceptions of distance learners in cyberspace. American Journal of Distance Education, Vol. 14, No. 2, pp. 15–35. Nogueira, J. &Machado, C., 2008. Teams in virtualclasses: An experiential perspective. Technology, Education, and Development. Retrieved at February 28, 2016 from http://www.intechopen.com/books/technology-education-anddevelopment/teams-in-virtual-classes-an-experiential-perspective Park, J.-H., & Choi, H. J., 2009. Factors Influencing Adult Learners' Decision to Drop Out or Persist in Online Learning. Educational Technology & Society, Vol. 12, No. 4, pp. 207–217. 135 ISBN: 978-989-8533-63-0 © 2017 Rovai, A. P., 2003. In search of higher persistence rates in distance education online programs. Internet and Higher Education, Vol. 6, No. 1, pp. 1–16. Sun, P.; Tsai, R.J.; Finger, G.; Chen, Y. & Yeh, D., 2008. What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, Vol. 50, No. 4, pp. 1183-1202. Yudko, E., Hirokawa, R. & Chi, R., 2008. Attitudes, beliefs, and attendance in a hybrid course. Computers & Education, Vol. 50, No. 4, pp. 1217-1227. Zawacki-Richter, O. & Naidu, S., 2016. Mapping research trends from 35 years of publications in Distance Education. Distance Education, Vol. 37, No. 3, pp. 1-20. 136 TEACHING QUANTITATIVE COURSES ONLINE: ARE LEARNING TOOLS OFFERED BY PUBLISHERS EFFECTIVE? Mohammad Ahmadi, University of Tennessee-Chattanooga Parthasarati Dileepan, University of Tennessee-Chattanooga Kathleen Wheatley, University of Tennessee-Chattanooga ABSTRACT In recent years, online teaching has become extremely popular. Most institutions of higher learning are offering online courses in almost every field of study. Teaching any course online is challenging, but teaching quantitative courses, such as operations management, management science, statistics, and others, have added a more challenging dimension to online teaching. Publishers have been assisting professors of quantitative methods courses by developing various teaching and evaluation tools. This study explores one such publisher’s tool, Quiz Me Mastery Points, of Pearson’s MyOmLab. The performance of students on their examinations and the Mastery Points they earned through the Quiz Me feature were compared, and it was determined that there was a significant correlation between the two. Keywords: Online teaching, Quantitative courses, Quiz Me Mastery Points, MyOmLab INTRODUCTION In the last decade online teaching and learning has become the norm in many institutions of higher learning. Numerous institutions are offering online courses both nationally and internationally. The Online Consortium tracks online education in the Unites States and releases an annual report entitled The Online Report Card. The most recently released report (Allen & Seaman, 2016) showed there were more than 5.8 million students in the United States enrolled in one or more online courses in the fall of 2014. This constitutes 28.4% of all student enrollment. The report further stated that many academic leaders (63.31% in 2015) strongly believe online learning is a critical component of their long-term strategy. It also stated that 77.14% of the chief academic officers in 2015 rated the learning outcome of online education as good as or better than face-to-face. However, an alarming finding was that only 29.1% of the chief academic officers believed their faculty accepted the value and legitimacy of online education. These findings, along with historic trends, reveal a mismatch between the growth in student demand for online course offerings and the hesitancy of faculty to buy into the efficacy of online teaching. Reconciling this mismatch is critical to realizing the full potential of the online classes that the students are increasingly expecting. Data were collected from students in an online MBA program (Kim, Liu, & Bonk, 2005) through semistructured, one-on-one interviews, surveys, and in-person focus group interviews. It was determined that over 70% of those surveyed described their online learning experience in a positive manner, and about 93% of the respondents were satisfied with the quality of their online courses. A study that conducted one-on-one interviews with fifteen experienced e-learning instructors (Bailey & Card, 2009) identified eight effective pedagogical practices for effective online teaching: fostering relationships, engagement, timeliness, communicJOURNAL OF EDUCATORS ONLINE ation, organization, tech-nology, flexibility, and high expectations. The challenge of understanding and integrating these eight facets of effective online teaching was a possible reason for the hesitancy within the ranks of the faculty to embrace online teaching (Allen & Seaman, 2016). Two key obstacles for effectively teaching an online class were identified as meeting the student’s core educational needs and maintaining a sense of teaching presence (Carliner & Shank, 2016). To meet students’ core needs, instructors must draw on a variety of tools and strategies, which various textbook publishers are increasingly offering. Among them are MyLab by Pearson, MindTap by Cengage, and Wiley Plus. Effective use of these tools can bridge the gap between student expectations and the hesitancy of faculty to meet the core needs of students. This paper explores and evaluates the Quiz Me Mastery Points of Pearson MyOmLab and determines whether this feature can bridge the gap between faculty hesitation and student demand for online offerings. We studied students’ performances on tests and the Mastery Points they earned through the Quiz Me feature and found that there is a significant correlation between the two. First, we present a comprehensive review of the current literature that deals with various challenges faced by online course offerings and what pedagogical responses were likely to be successful. Then, in the methodology of the study we investigate the performance of 174 students over four semesters (3,000 individual assessment scores). Next, we give the results of the analysis and we identify factors that improve or do not have an impact upon student performance. Finally, we propose possible avenues for future research. LITERATURE REVIEW In recent years, blended teaching and learning, which includes online versus face-to-face, has grown immensely; yet, the literature is not as abundant as one would expect. Not only has learning been under scrutiny, but some studies have focused on other students’ and teachers’ viewpoints such as satisfaction, performance, professor-student interaction, and a host of other facets of teaching and learning. Smith and Bryant (2009) observed the paucity of literature on teaching case-based statistics classes and offer useful JOURNAL OF EDUCATORS ONLINE tips for guiding online discussions. Dotterweich and Rochelle (2012) also lamented the paucity of research examining student characteristics and factors leading to successful outcomes. They studied three modes of delivery (online, instructional television, and traditional classroom) with three groups of students with similar GPAs prior to taking their statistics courses. They found online students were significantly older and more likely to repeat the course and have earned more credit hours prior to enrolling. They also found that GPA and percentage of absences were highly significant predictors of course performance. On the suitability of online delivery for quantitative business courses, specifically business statistics and management science, research findings suggest that features involving professor-student interaction are the most useful, features promoting student-student interaction are the least useful and discussion forums are of limited value in learning quantitative content (Sebastianelli & Tamimi, 2011). Katz and Yablon (2003) examined students’ academic performance in a required first-year university internet-based Introduction to Statistics course and the psychopedagogical variables that contributed to students’ online learning as compared to the learning of students who participated in a traditional lecture-based course. They found no difference in the performance levels achieved by students of the two groups. In addition, they found that participation in the online course improved psychopedagogical attitudes towards online learning despite the initial misgivings of the participants in. A meta-analysis of performance differences between online and face-to-face undergraduate economics courses in the United States (Sohn and Romal, 2015) found statistically significant and stronger performances for face-to-face instruction. Further, the study found older/mature online instruction enrollees performed better. Concerning satisfaction, a survey of students of an online statistics course found positive satisfaction with a mean of 4.00 in a fivepoint Likert-scale (Al-Asfour, 2012). The study demonstrated that students were satisfied with online instructions, communications, and assessments. On the question of students’ perceptions of online homework assignments, a study of an introductory finance class discovered that, in general, students preferred online homework to traditional homework. The study further determined that students found that the homework assignments increased their understanding of the material and graduate students reported a higher level of satisfaction than did undergraduates (Smolira, 2008). Law, Sek, Ng, Goh, & Tay (2012) examined students’ perceptions of the use of the Pearson’s online learning platform MyMathLab as a supplementary tool in conducting assignment and assessment in a mathematics course and found that overall the students were satisfied with the use of the MyMathLab platform. Alrushiedat and Olfman (2013) conducted a field experiment that explored the potential benefits of asynchronous online discussions for business statistics classes and found they facilitated more and better-quality participation and engagement for undergraduates. Walstrom (2014) compared the performance and satisfaction of over 220 students enrolled in a traditional face-to-face class and over 300 students in an online class while migrating an Electronic Business Management course from a traditional face-to-face delivery to an online delivery across a six-and-a-half-year period. The comparison revealed that student performance and satisfaction remained mostly consistent across delivery methods. Nicholson and Nicholson (2010) surveyed student and faculty perceptions of using streaming video for teaching students Microsoft Excel and Access skills in an introductory management information systems course. The results from the survey showed that the use of a multimedia component to convey course material provided benefits to students in the form of greater satisfaction with the learning process, a greater understanding of the material, as well as a reduction in the effort required to complete homework assignments. They further reported that the instructors experienced a marked reduction in visits from students who required additional exposure to previously covered material, a decrease in prep time during subsequent semesters, and seamless portability to online learning contexts. Fuller and Bail (2011), using an action research model, described the outcomes of an interactive team-teaching model while teaching an online graduate-level disaster research and statistics course during a span of five semesters. They reviewed instructor reflective logs and student responses to the team-teaching model and found that there was a positive benefit in developing synergy in content and pedagogies, continued instructor learning, and continuous reflection on instructional design. They further found that the immediacy of feedback and the added access and clarity of the team-teaching process resulted in students reporting a greater understanding of the research and statistical process. Hegeman (2015) examined whether student performance in an online College Algebra course could be improved if instructor-generated video lectures were used instead of publisher-generated educational resources. The study involved a College Algebra course that used all the publisher-generated educational resources and another course in which students completed instructor-generated guided note-taking sheets while watching instructorgenerated video lectures with publisher-generated learning aids available as supplemental resources. The results of this study showed that strategically placing instructor-generated content improved student performance significantly on both online and handwritten assessments. The effectiveness of the videoconferencing software Blackboard Collaborate for carrying out instruction at the college level to students attending classes synchronously at multiple locations was evaluated by Tonsmann (2014) and found to be an effective method for educating students at a distance. A multiple regression analysis used a dataset that included over 5,000 courses taught by over 100 faculty members over a period of ten academic terms at a large, public, four-year university (Cavanaugh & Jacquemin, 2015). This study revealed a statistical difference among course formats that amounted to a negligible difference of less than 0.07 GPA points on a four-point scale. The authors further found an interaction between course type and student GPA, indicating that students with higher GPAs performed even better in online courses. Alternatively, struggling students performed worse when taking courses in an online format compared to a face-to-face format. Pena-Sanchez (2009) examined whether the course delivery method, online or face-to-face, and gender affected academic progress. Through chi-square tests, it was found that the population proportion of successful students in a course of JOURNAL OF EDUCATORS ONLINE Business Statistics did not depend on their gender or the delivery mode of the class. Wiechowski and Washburn (2014) studied more than 3,000 end-of-semester course evaluations collected from 171 finance and economics courses in the 2010-2011 academic year. They reported that the online and blended courses had a stronger relationship with high course satisfaction than did face-to-face courses. Further, they stated that there was no significant relationship found among student learning outcomes and the mode of course delivery. Peng (2015) used an ordinary least squares regression model to analyze a sample of 206 students during the period from 2008 to 2012 and found that significant predictors of student performance were age, major, degree obtained, and the number of hours a student worked but not the choice of a more readable textbook. Calafiore and Damianov (2011) used the online tracking feature in Blackboard (Campus Edition) to retrieve the real time that each student spent in the course for the entire semester and to analyze the impact of time spent online, prior grade point average (GPA), and other demographic characteristics of students on their final grades. They found that both time and GPA were significant determinants of the final grade. Chen, Jones, and Moreland (2010) surveyed students in online and traditional classroom sections of an intermediate-level cost accounting course on several items related to instruction and learning outcomes. Then, they compared the student examination performance in the two types of sections. They found that both learning environments generally had similar ratings. However, where there was a difference, the satisfaction level of students in the traditional classroom was higher. Furthermore, they stated that the examination performance for 14 of 18 topic areas were similar with the traditional method producing better comprehension in three of the remaining four areas. METHODOLOGY The opportunities thrown open by the increasing popularity of online courses comes with difficult challenges. They include technical challenges such as mastering software platforms for content delivery, interacting with students, online content delivery, participation, assessment, learning style, time management, and motivation. JOURNAL OF EDUCATORS ONLINE There are technical solutions for many of these challenge and publishers offer learning platforms for popular textbooks. Quantitative courses present tough challenges when they are offered online. Mastering quantitative aspects of problem solving is critical. Publisher online platforms have modules that provide the opportunity for students to practice and master concepts before taking tests. Pearson’s MyOmLab platform includes several tools that can be used for practice and learning concepts as well as assessments. They include Practice, QuizMe, Homework, Quiz, and Test. As students work on each section of the chapters of the textbook and achieve a minimum score in a combination of assessment tools set by the instructor, the students earn a Mastery Point. In this study, three tools were used: Practice, QuizMe, and Chapter tests. Students can learn concepts and problem-solving skills by using the practice tool, which allows students to seek help from a variety of sources including reaching out to the instructor. The QuizMe tool allows students to self-test at the level of mastery achieved by using the practice tool. In this study, we set the minimum threshold of 80% in the QuizMe for students to earn the Mastery Points associated with the section. If a student failed to achieve the minimum score, she or he could go back to Practice and then retake the QuizMe until earning the Mastery point. In as much as students can seek help while using Practice and repeat QuizMe unlimited times, Mastery Points earned had half the weight of chapter tests that were similar in content, but students could not receive any help and had only two attempts with the higher of the two grades recorded. One of the research questions we faced was whether this process of earning Mastery Points with unlimited trials of Practice and QuizMe was helping student performance as measured by chapter tests. Further, we had both undergraduate and graduate classes in the pool of classes for which we gathered data (further described in the next section). Therefore, we formulated the following four hypotheses: Hypothesis 1: H0: The Mastery Score in a given chapter does not have any effect on the test score in the corresponding chapter. HA: The higher the Mastery Score in a given chapter the higher the test score will be in the corresponding chapter. Hypothesis 2: H0: The time spent earning Mastery Score in a given chapter does not have any effect on the test score in the corresponding chapter. HA: The higher the time spent earning Mastery Score in a given chapter the higher the test score earned in the corresponding chapter. Hypothesis 3: H0: The average chapter test scores for graduate students are the same as the corresponding average for undergraduate students. HA: The average chapter test scores for graduate students are higher than the corresponding average for undergraduate students. Hypothesis 4: H0: There is no interaction course level and Mastery Score average chapter test scores. HA: There is an interaction course level and Mastery Score average chapter test scores. effect between earned on the effect between earned on the Our study included 174 students over a period of four semesters. For each of the 174 students, data were collected on five variables for each of the nine chapters listed in Table 1. These variables are shown in Table 2. Note the Mastery Score recorded was the percentage of total mastery points available for the given chapter. Similarly, the test scores were converted to a 100-point scale for consistency. Table 2. Variables for the Nine Chapters Variable Course level Description Variable Graduate or Undergraduate Course level Assessment chapter Chapter Mastery Score Percentage of subsections of the chapter mastered Mastery Score Mastery Time Time spent mastering the chapter Mastery Time Test score (0–100) Test Score Description Variable Graduate or Undergraduate Course level Assessment chapter Chapter Percentage of subsections of the chapter mastered Mastery Score Chapter Test Score Variable Course level Chapter Mastery Score THE DATA We chose Operations Management at the undergraduate level and Production and Operations Management at the graduate level. While there were significant differences in the range and coverage of topics between the undergraduate and graduate classes, we identified nine core chapters that were common to both levels of classes. They are given in Table 1. THE RESULTS The summary of results is presented in Table 3. Figure 1 shows a scatter plot of average chapter Mastery Score of individual students against their respective average test score. The graduate student scores are plotted with ● and the undergraduate student scores are plotted with *. The scatter plot shows a positive relationship between the level of mastery achieved and test score. Further, there is a clear separation of average scores between the graduate and undergraduate students. Table 1. Chapters Common to OM and POM Table 3. Average Mastery and Test Scores Chapter Description Mastery Points Graduate Mastery Score Undergraduate Test Score Productivity 98.46 94.44 7 Project Management 96.27 90.80 Managing Quality 6 Forecasting 91.89 93.13 1 Productivity 10 2 Project Management 10 3 Forecasting 4 Chapter 5 Statistical Process Control 3 Managing Quality 98.83 93.64 6 Inventory Management 7 Statistical Process Control 85.45 87.42 7 Aggregate Planning 7 Inventory Management 90.56 81.49 8 Materials Requirement Planning 8 Aggregate Planning 92.98 92.87 9 Scheduling 7 Materials Requirement Planning 94.08 87.17 JOURNAL OF EDUCATORS ONLINE Table 4. Results of Overall Regression Analysis of Variance Source DF Sum of Squares Mean Square F Value Pr > F 174.81
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Check this on qualitative and recommend and enhancement...am fixing quantative paper

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Community Based Participation in Iran

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Community Based Participation in Iran

A qualitative study of community-based health programs in Iran

Introduction

Community-based health programs (CBHPs) have been reported to an essential and
recognized tool in health promotion. This study aimed to evaluate as well as understanding the
nature of participation practice in CBHP. Through this study, the data obtained is used to
advocate for more participation-friendly policies in the community. The research shows to
develop a healthy community, the overcoming of complex and problems calls for participatory
approaches and solutions that bring the community together, be it being a governmental or nongovernmental organization. The rationale for promoting and pursuing community participation
includes advocating behavior change, improving service delivery to the people, and mobilizing
resources such as health services, financial and other materials (The World Health Organization.
(2017).
Participation can be termed to a process whereby members of a particular community
come together with an aim or plan of assessing their health issues and problems and finding
proper ways of dealing with them. According to the study, there is an effectiveness increment, as
evidenced by the improvement of health concerns and even people participating in treatment
decisions.
In Iran, various CBHPs have been formed by both government and non-government
organizations, all having an aim f improving health systems in that country. The recent research

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Community Based Participation in Iran

is part and parcel of documenting comprehensive investigations on the experiences obtained
from different parties involved in CBHP projects. This study sought to explore the expertise of
the partners concerning participation practice in Iran (Barati, Abu, Ahmad, & Idris, 2013).

Methodology

The investigation conducted used a qualitative method. The method is practically proven
to give insights to the participants'' expertise. As part of the data collection, the interview method
was considered to be the most effective way of collecting raw and primary data from different
respondents. Focus group discussions (FGDs) were conducted with volunteers due to its
usefulness in matters of group opinions, experience, attitude, and knowledge (The World Health
Organization. (2017).

Realization of the research

To implement this in expertise manner, a group of advisory committees was born to
oversee the process of the study. The group was comprised of CBHPs managers, WHO
representatives, and Researchers. For the recruitment of the members of the committee,
knowledge and expertise are key factors to consider. 13 programs were chosen by the committee
based on two criteria, which are being active program in the recent 5yrs and having the
community-based characters (Barati, Abu, Ahmad, & Idris, 2013).

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Community Based Participation in Iran

Study participants and sampling process

Participants’ selection was made purposively from each of the programs with vital
assistant persons who are expertise in programs for a long time. For each of the programs, two
interviews with a program principal and executive managers. In total, 102 were conducted for
responding to the interview. The focus group made up both of men and women, each consisting
of 5-8 participants.

The process of conducting the interview

The team purposed to conduct the interview constituted six researchers with prior
knowledge in qualitative research as well as interviewing methods. During the interview, a 4hrs
session was set aside for explaining the probable problems which might be incurred during the
implementation phase.
After the introduction, the moderator provided an explanation about community health
participation and later asked to know more about CHBP components. During the interview, the
respondents were encouraged to be open about their experience relating to the programs. For...


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