在线学习环境中课程完成原因探析(英文)

很多提供在线课程的教育机构所面临的一大挑战就是开发能够提高学生动机的教学策略,从而提高课程和项目的完成率.本研究利用Eastmond(1994)开发的"基于计算机会议的成人远程学习框架"(Adult Distance Study through Computer Conferencing,简称ADSCC),探讨了学习者的准备情况、在线特征、与计算机媒介传播(Computer Mediated Communication,tuj tq CMC)相关的学习方法等因素是否会影响虚拟学习环境中学生自备课程完成情况.研究结果表明,以上因素与课程完成情况有着显著的正相关.同时研究还发现,自我动机、对技术的信任,以及技术的易用等是在线学习环境中课程完成的主要原因.     

Predicting student satisfaction and perceived learning within online learning environments

Student satisfaction is used as one of the key elements to evaluate online courses, while perceived learning is considered as an indicator of learning. This study aimed to explore how online learning self-efficacy (OLSE), learner–content interaction (LCI), learner–instructor interaction (LII), and learner–learner interaction (LLI) can predict student satisfaction and perceived learning. A total of 167 students participated in this study. Regression results revealed that the overall model with all four predictor variables (OLSE, LCI, LII, and LLI) was significantly predictive of satisfaction and perceived learning. The study found that LCI was the strongest and most significant predictor of student satisfaction, while OLSE was the strongest and most significant predictor of perceived learning. However, LLI was not predictive of student satisfaction and perceived learning. This study suggests that instructors employ strategies that enhance students’ OLSE, LCI, and LII. Research is needed to understand how LLI fosters student learning and satisfaction.     

The effects of need satisfaction on EFL online learner satisfaction

This study explored the effects of need satisfaction (autonomy, competence, and relatedness) on English as a foreign language (EFL) online learner satisfaction and validated the Chinese versions of the need satisfaction scale (NSS) and online learner satisfaction scale (OLSS). We collected data from a questionnaire administered to 199 EFL students at a Taiwanese university. The Cronbach’s alpha reliability coefficient for NSS was .90 and .91 for OLSS. For NSS, the principal component analysis (PCA) resulted in a three-factor solution that accounted for 61.31% of the variance. Regarding OLSS, PCA resulted in a two-factor solution that accounted for 63.17% of the variance. A multiple regression analysis revealed that three independent variables (autonomy, competence, and relatedness) were predictors of EFL online learner satisfaction (F(3,?191) = 85.14, P < .001, R² = .57), with competence the best predictor of online learner satisfaction, followed by relatedness and autonomy. The paper concludes with implications of these results.     

The Relationships Between Academic Self-Efficacy,Computer Self-Efficacy,Prior Experience,and Satisfaction With Online Learning

This study investigated the relationships between academic self-efficacy (ASE), computer self-efficacy (CSE), prior experience, and satisfaction with online learning and explored how ASE, CSE, and satisfaction vary with age and gender. One hundred and three graduate students enrolled in purely online courses in January 2014 at a university in the midwestern United States participated in the survey. Scales with known reliability were used to measure ASE, CSE, and satisfaction. The study showed a significant positive correlation among all the variables except CSE and satisfaction. Regression analysis showed ASE to be most predictive of satisfaction with online learning. Females had a higher mean ASE than males, and participants aged thirty-five years and above had a higher mean CSE than younger participants.     

Online learning experiences of new versus continuing learners: a large-scale replication study

A vast body of research has indicated the importance of distinguishing new vs. continuing students’ learning experiences in blended and online environments. Continuing learners may have developed learning and coping mechanisms for ‘surviving’ in such learning environments, while new learners might still need to adjust their learning approaches to the new learning context. In this large-scale replication study, we investigated whether and how the learning satisfaction experiences of 16,670 new vs. 99,976 continuing students were different. Using logistical regression modelling of learner satisfaction scores of 422 undergraduate blended and online modules (including 232 learner and module learning design variables), our findings indicated that new learners indeed differed subtly in their learning and teaching experiences across two consecutive academic years. The minor differences in key drivers between the 2014 and 2015 cohorts also indicate that institutions need to continuously monitor and act upon changing learning needs.     

Accelerated Online Learning: Perceptions of Interaction and Learning Outcomes Among African American Students

This study investigated student interaction, satisfaction, and performance in accelerated online learning environments with the use of an online learning course-management system. The interactions assessed in this study included learner–learner interaction, learner–instructor interaction, and learner–content interaction. The participants were African American students from a university in the southeastern United States. Quantitative approaches including correlation and regression analyses were performed to examine the contribution of interaction predictors to student satisfaction as well as the relationship between student satisfaction and student performance. In addition, Internet self-efficacy and its impact on interaction was investigated. The results showed that learner–content interaction was the only significant predictor of student satisfaction whereas interaction among students or with the instructor did not significantly predict student satisfaction. Internet self-efficacy was positively correlated with three types of interaction. Student satisfaction was found to be related to student performance.     

Exploring the link among entry characteristics,participation behaviors and course outcomes of online learners: An examination of learner profile using cluster analysis

Online learner profiles have diversified such that now, they include all types of participants from a variety of backgrounds. This study analyzed online learner profiles in regard to their entry characteristics, participation behaviors and achievement of course outcomes. The sample consisted of 186 participants from an online course that required the employment of synchronous and asynchronous communication methods over the Internet. The data were collected through five online questionnaires and included 10 variables (gender, age, work status, self‐efficacy, online readiness, self‐regulation, participation in discussion list, participation in chat sessions, satisfaction and achievement). A two‐step cluster analysis, chi‐square analysis and multivariate analysis were used to analyze the collected data. The results indicated that online learners fell into three significantly different clusters and within each cluster, learners had a close combination of employment characteristics, gender type, age level, perception of self‐efficacy for online technologies and participation behavior level.     

Learner Satisfaction with Massive Open Online Courses

This study investigates factors that influence learners’ satisfaction with massive open online courses (MOOCs). Framed by the theory of independent learning and teaching, the three types of interaction model, and the technology acceptance model, this study analyzed data collected from 1,786 learners enrolled in four MOOCs. Results show that the learner perceived usefulness, teaching and learning aspects of the MOOC, and learner-content interaction as important satisfaction factors. Learner-learner interaction and learner-instructor interaction had no effect on the sample’s learner satisfaction with the MOOC. These findings improve our understanding of MOOC learners’ preferences and contribute to the process of designing and developing new MOOCs. Future directions in MOOCs’ development are also discussed.     

基于学习认知地图的开放学习者模型研究

学习者模型是自适应学习系统的重要组成部分,然而传统的学习者模型往往是封闭的,学习者无法知晓模型的具体内容。文章从学习者模型内容开放的视角,设计了能够表征学习者认知状态和知识结构并推送学习路径与学习同伴的开放学习者模型——学习认知地图。基于学习元平台,文章从认知状态评测、知识结构计算和可视化呈现三个方面对学习认知地图的构建过程进行了阐述。之后,文章将构建的学习认知地图应用于中学信息技术课堂,实践结果表明:学习认知地图能够提升学生的学习态度,同时学生对具有学习认知地图支持的在线学习方式满意度更高。文章设计并检验了作为一种开放学习者模型实践样态的学习认知地图的效果,以期为开放学习者模型的进一步研究提供参考。     

The effect of learning style on preference for web‐based courses and learning outcomes

As the number of courses offered online increases rapidly, it is important for teachers and institutions to identify specific learner characteristics of successful online students. This paper reports on a study that compared an online group of freshmen computer science majors with an equivalent on‐campus group to find if their individual learning styles play a role in the selection of course delivery mode (online or face to face) and in their academic achievement. No significant statistical differences were detected in learning styles and learning performance between the two groups. Implications for teaching practice and design of learning activities that resulted from this study are discussed.     

Enhancing learner–learner interaction using video communications in higher education: Implications from theorising about a new model

As visual connectivity improves, an opportunity to enrich and rethink the place of learning design in online and distance education is presenting itself. The opportunity is derived from the increasing scope for personalised synchronous interaction which has been missing in computer mediated communications (CMC) and previous generations of distance education. This paper presents a model which distinguishes between planned learner‐content interaction and learner‐learner interaction and suggests that a blend of planned and non‐planned learner‐learner interaction is worthwhile. It concentrates on technology enhanced learning using video communications which provide opportunities for more authentic online collaborative learning, formally and informally. This conceptualisation is underpinned by beliefs which promote constructivist and transformative learning in the hope of stimulating debate as universities focus more towards quality learning. The intent is to explore the implications of learning in higher education becoming enhanced in online environments as learner‐learner dialogue occurs ‘face‐to‐face’, thus, extending the potential of online learner‐content environments.     

Tutoring styles that encourage learner satisfaction,academic engagement,and achievement in an online environment

This study was aimed to find which tutoring styles significantly predict learners’ satisfaction with an e-learning service, academic involvement, and academic achievement. The tutoring styles included subject expert, facilitator, guider, and administrator. In this study, 818 Korean sixth-grade students (ages 11–12 years), enrolled in the e-study program, and completed tutoring style and academic satisfaction evaluation surveys. Students’ login and posting frequency in the e-study program were measured to assess their academic involvement. Academic achievement was computed using completion rates and assessment scores. Multiple regression analyses indicated that there is some association between tutoring styles and academic outcomes. Of the four tutoring styles, facilitating tutoring styles particularly showed strong associations with the three outcome variables. Tutors’ guiding activities as opposed to facilitating were not significant contributors to students’ academic outcomes. The effect of tutors’ facilitating styles in an online learning environment was significant as being found in the existent literature.     

Learner Autonomy and Selected Demographic Characteristics as They Relate to Life Satisfaction Among Older Adults in Malaysia

Malaysia currently has about three million senior citizens. United Nations statistics show that Malaysia is likely to reach aging nation status by the year 2035. It is important to address the issues that may have impact on the needs and concerns of this growing population. This study examined the relationships of life satisfaction, learner autonomy, and selected demographic variables of older adults in the state of Kelantan, Malaysia. A convenience sample of 111 adults, age 50 or older, participated in this survey. Statistical analyses assessed relationships of demographic variables to Learner Autonomy Profile and Life Satisfaction Scores. Findings reveal ethnicity, education level and living area correlate significantly with the learner autonomy scores. Only education level was found to significantly correlate with life satisfaction. Results indicate a significant relationship of learner autonomy scores and life satisfaction scores. Implications for practice and recommendations for further study and public policy emphases are discussed.     

Self-regulatory and demographic predictors of grades in online and face-to-face university cohorts: A multi-group path analysis

Predictors of academic success at university are of great interest to educators, researchers and policymakers. With more students studying online, it is important to understand whether traditional predictors of academic outcomes in face-to-face settings are relevant to online learning. This study modelled self-regulatory and demographic predictors of subject grades in 84 online and 80 face-to-face undergraduate students. Predictors were effort regulation, grade goal, academic self-efficacy, performance self-efficacy, age, sex, socio-economic status (SES) and first-in-family status. A multi-group path analysis indicated that the models were significantly different across learning modalities. For face-to-face students, none of the model variables significantly predicted grades. For online students, only performance self-efficacy significantly predicted grades (small effect). Findings suggest that learner characteristics may not function in the same way across learning modes. Further factor analytic and hierarchical research is needed to determine whether self-regulatory predictors of academic success continue to be relevant to modern student cohorts.

Practitioner Notes

What is already known about this topic

• Self-regulatory and demographic variables are important predictors of university outcomes like grades.
• It is unclear whether the relationships between predictor variables and outcomes are the same across learning modalities, as research findings are mixed.

What this paper adds

• Models predicting university students' grades by demographic and self-regulatory predictors differed significantly between face-to-face and online learning modalities.
• Performance self-efficacy significantly predicted grades for online students.
• No self-regulatory variables significantly predicted grades for face-to-face students, and no demographic variables significantly predicted grades in either cohort.
• Overall, traditional predictors of grades showed no/small unique effects in both cohorts.

Implications for practice and/or policy

• The learner characteristics that predict success may not be the same across learning modalities.
• Approaches to enhancing success in face-to-face settings are not automatically applicable to online settings.
• Self-regulatory variables may not predict university outcomes as strongly as previously believed, and more research is needed.

     

Learning online,offline, and in-between: comparing student academic outcomes and course satisfaction in face-to-face,online, and blended teaching modalities

The purpose of this study was to conduct a three-way comparison of face-to-face, online, and blended teaching modalities in an undergraduate Child Development course to determine if there were differences in student academic outcomes and course satisfaction across modalities. Student academic outcomes were measured by three examinations, one research paper assignment, and the overall course total grade. Course satisfaction was measured by administering the Student Opinion Questionnaire (SOQ) across the three teaching modalities and the Constructivist On-Line Learning Environment Survey (COLLES) to online and blended modalities. Results indicated that students performed equally well on all three examinations, research paper, and the overall course total grade across three teaching modalities, allaying traditional reservations about online and blended teaching efficacy. The SOQ and COLLES analysis found students from the three modalities were equally satisfied with their learning experiences. A Two-Factor Model identifying Face-to-Face Interaction and Learn on Demand (Flexibility) as factors determining student academic outcomes was proposed. Implications, limitations, and future research direction were discussed.     

Computer Self-Efficacy and Motivation to Learn in a Self-Directed Online Course

Despite the increased use of new learning technologies, there is still much to be learned about the role of learner characteristics in online learning. The purpose of this study was to examine how subjects' characteristics normally associated with effective training (i.e., initial motivation to learn and self-efficacy) related to learning in a self-directed online course. From an analysis of 190 respondents, computer and Internet usage prior to the start of class were positively related to individuals' computer self-efficacy and computer self-efficacy was positively related to learning. However, contrary to expectations, computer self-efficacy was not related to initial motivation to learn and motivation to learn was not related to learning in the class. Post hoc analysis of qualitative data enabled a rich explanation of the findings, including an evaluation of the unexpected relationships among the variables of interest and the nature of self-directed courses in virtual learning environments.     

K-12 teachers’ perceptions of and their satisfaction with interaction type in blended learning environments

Blended learning is an effective approach to instruction that combines features of face-to-face learning and computer-mediated learning. This study investigated the relationship between student perceptions of three types of interaction and blended learning course satisfaction. The participants included K-12 teachers enrolled in a graduate-level course. Results indicate that students (a) perceived interaction as important to their learning experiences and (b) were moderately satisfied in their blended learning course. The predictive model of student satisfaction including three types of interaction was reliable. Of the three types of interaction, learner–content interaction was the strongest predictor of student satisfaction when the course design involved a low amount of collaborative activities. Additionally, student personality was found to be a vital factor for interaction and satisfaction in this type of course design. Students who reported having an extroverted personality noted more interaction and a higher level of student satisfaction than those who self-reported as introverted.     

Exploring student perceptions of group interaction and class satisfaction in the web-enhanced classroom

This paper presents an exploratory study of a web-enhanced televised class encouraging learner–learner interaction in small online groups. The purpose of the study was to examine whether various interactions among students in small groups could substitute for one-on-one interaction between the instructor and each student and lead to high levels of perceived class interaction and student satisfaction. It was found that perceptions of overall class interaction and student satisfaction seem to be positively affected by small group interaction. Implications for research and practice are discussed.