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Measuring student mental readiness for flipped blended learning: Scale development and validation
... Thus far, several technology-related scale development studies (e.g. Hung, 2016;Hung et al., 2010;Zhou et al., 2017) have incorporated self-efficacy as one of the dimensions to measure readiness. It is crucial to assess mobile self-efficacy when investigating readiness considering that m-learning deals with the use of technology, particularly mobile technology. ...
Background:
The application of mobile learning (m-learning), especially in the area of language learning, has gained interest in the last several years due to the benefits offered by mobile devices. However, to maximize the effectiveness of m-learning, students are required to be ready. Thus, it is crucial to assess students’ readiness before implementing m-learning. By focusing on rural schools, this quantitative study aims to examine students’ readiness in implementing m-learning in their English language learning.
Methodology:
This study employed a survey design to measure m-learning readiness of senior high school students by investigating three factors, namely mobile self-efficacy, optimism, and self-directed learning. Through an online questionnaire, 140 responses were successfully collected from students in two public senior high schools (one high school and one vocational high school) located in a rural area in Soppeng, Indonesia. The data collected were subsequently analyzed using SPSS Statistics ver. 25.
Findings:
The results revealed that senior high school students from a rural area in Soppeng, Indonesia, had a high level of self-efficacy and optimism in implementing m-learning in their English language learning. However, their self-directed learning was still at a moderate level. Moreover, further analysis showed that type of school significantly affected students’ mobile self-efficacy and optimism, while self-directed learning was not affected.
Conclusion:
Students from rural senior high schools in Soppeng, Indonesia, showed readiness in implementing m-learning for English language learning purposes.
... The ease and on the go availabilityof digital platforms or resources has led into digitization of higher education in India. The availability of learning videos and online courses has made transformation in the traditional approaches of educational institutions of higher education [6]. This paper tries to identify the inclinationof students to take up blended learning and measure effectiveness of blended learning. ...
Blended learning is one of the most evolving teaching learning pedagogy. Educational institutions across disciplines are adopting the blended learning environment.. The new generation of students also known as millennials are digital natives. They are tech competent and prefer to use of technology in all areas. So it is very natural for teaching learning to be more technology oriented. But it is still essential to identify the willingness of the students to adopt the digital transformation in teaching learning.. Blended learning brings in the advantages of both traditional class room teaching and online or virtual learning. The current study tries tounderstand students’ willingness for a blended learning model approach and also tries to finds the effectiveness of blended learning model.
... On the other hand, there has been increasing pressure for the educational community to undergo a transformation that allows for flexible solutions that support teaching objectives, provide students with new activities, increase opportunities for active learning in the classroom, and improve students' digital literacy and lifelong skills [27]. ...
Nowadays, several institutions and universities have employed Flipped and Blended Learning models in the educational context. Consequently, these models advance correctly in the classrooms; students become more able to build their knowledge and develop their skills with technological innovation that could be compared with studies based on technological achievements and accessible data Tics. Therefore, this article proposes educational innovation in the evaluation processes within the FL and BL learning models to ensure active and interactive education. In this work, a bibliometric analysis of 2000 scientific articles from the Web of Science and Scopus databases has been carried out, thus making it possible to identify countries and universities with constant and relevant use of these learning models, as well as a comparison with these databases of articles, citations and their global impact. On the other hand, a survey was conducted with 41 teachers of different subjects and 385 students from elementary school to high school using the Likert scale. The questions were represented in perception values with their respective analysis of results and evaluations about these learning models, technological resources, flexible curriculum, learning before class, autonomous learning, and future professional competencies, which will help us know the existing motivation between them.
... b Attitude towards online flipped learning. Students' attitude towards online flipped learning was assessed using the 4-item scale adapted from the scales by Zhou et al. (2017). This scale aimed to evaluate the tendency and preference that students attributed to online learning as compared to traditional classes. ...
As one variant of the conventional flipped model, online flipped learning is increasingly implemented and it becomes important to explore how learners may be ready for it and how learner readiness may relate to motivation, attitude, and support. Informed by a multidimensional conceptualization of learner readiness and motivation and engagement, this study investigates the current situation of learner readiness, focusing on the moderating roles of learner attitude and environmental support in moderating the interrelationships between learner readiness and motivation and engagement in online flipped learning. Based on survey responses from 6,364 English learners across 11 Chinese universities, the results reveal that the students exhibited a generally high level of readiness for online flipped learning, though with significant demographic differences. The results also indicate that learner attitudes and environmental support moderated the impact of learner readiness upon learner motivation and engagement in online flipped learning. The findings call for attention to examine closely what dimensions of learner readiness could shape what aspects of motivation and engagement rather than simply assuming a linear causal relationship between readiness and motivation and engagement. A potential polarizing effect in online flipped learning is also highlighted, with implications discussed.
The aims of this research are to investigate the extent of the constructivist learning environment integration in science classrooms and students’ perceptions of their actual and preferred learning environments in science learning. Additionally, this research aims to assess educational facilities in schools and identify its relationship with constructivist learning environment. Actual and preferred form of Constructivist Learning Environment Survey (CLES) and Learning Environment Assessment (LEA) were used in this research. The instruments were administered to 150 Form Four science students from 3 schools in Bidor, Perak. The data were analysed quantitatively for the research questions. The result showed that students agreed to most of the scales in actual form of CLES except the scale Shared Control in which they were not invited to share teacher's control in planning learning environment. T-test showed that students tended to prefer more constructivist learning environment than the actual learning environment (p<0.05). Besides, the result showed that subsection Academic Learning Space in LEA was at the level of minimal adequacy whereas subsection Interior Environment showed the level of moderate adequacy. Simple correlation analysis showed that LEA was positively related to actual form of CLES (r=0.22). The finding suggested that science teachers should implement the constructivist approach and improve their practice based on students’ preference of learning environment to improve students’ performances. Also, educational facilities were suggested to be assessed to ensure the success of the integration of constructivist learning environment in the science classrooms.
Self-efficacy is defined as the belief that one can successfully perform a behavior. Self-efficacy theory asserts that self-efficacy expectancies exert powerful influence on behavior and behavior change. The Self-efficacy Scale, which was developed to assess generalized self-efficacy expectations, consists of two subscales: general self-efficacy and social self-efficacy. To provide further evidence of the construct validity of the Self-efficacy Scale and to investigate the relationships between the Self-efficacy subscales and other personality measures, i.e., the Minnesota Multiphasic Personality Inventory (MMPI), the Rathus Assertiveness Schedule, and the Bem Sex Role Inventory, introductory psychology students (N=101) completed all four measures. Analyses of results showed that high scorers on the General Self-efficacy Subscale exhibited better adjustment, as measured by the D, Pt, and Si scales of the MMPI, than low scorers. Higher scores on both subscales were associated with increases in assertiveness and masculinity as measured by the Rathus schedule and the Bem inventory. The results support the interpretation of the Self-efficacy Scale as a measure of expectancies of personal ability to initiate and persist in the performance of behaviors. Positive self-efficacy expectancies contribute to enhanced personal adjustment. The General Self-efficacy Subscale appears to be more useful than the Social Self-efficacy Subscale. (Author/WAS)
The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addition to the known problems related to sample size and power, is that it may indicate an increasing correspondence between the hypothesized model and the observed data as both the measurement properties and the relationship between constructs decline. Further, and contrary to common assertion, the risk of making a Type II error can be substantial even when the sample size is large. Moreover, the present testing methods are unable to assess a model's explanatory power. To overcome these problems, the authors develop and apply a testing system based on measures of shared variance within the structural model, measurement model, and overall model.
This study surveyed 387 middle school 7th – graders' flipped learning readiness in their English-as-a-foreign-language (EFL) classrooms and explored the effects of personal characteristics on their readiness levels. These personal characteristics included gender, the availability of outside-school support and resources, foreign language beliefs, perceptions of their English teachers, and how they use the Internet. Through factor analysis, flipped learning readiness consists of five dimensions: learner control and self-directed learning, technology self-efficacy, motivation for learning, in-class communication self-efficacy, and doing previews. It was found that personal characteristics and individual circumstances, including language beliefs, student perceptions of teacher characteristics, the availability of outside-school support and resources, learning performance, study time and net-surfing time, can make a difference to the levels of the readiness dimensions. These findings may shed light on the middle schoolers' flipped learning readiness in EFL classrooms and provide insights for teachers wanting to incorporate individualized instruction in the flipped classroom.
This study surveyed 84 undergraduate students, majoring in education, in order to gather their perspectives regarding flipped classrooms and investigate their readiness levels for flipped learning. After the implementation of flipped learning for an entire semester, surveys were distributed in two flipped classrooms that were taught by the same instructor. Students showed particular preferences for the “Bring Your Own Device” and the Instant Response System features of the flipped classroom. Approximately 60% agreed with the idea of flipped classrooms, but only 39% agreed that the flipped classrooms met their learning needs. Their readiness levels for flipped learning were moderately above the average levels, and males or juniors (compared with freshmen), felt more prepared for flipped learning. In general, course grades, self-directed learning readiness, and group work preference can predict the different readiness dimensions. The findings may enhance educators' understanding in how to apply the flipped learning model in ways that are most beneficial for their own students.
The flipped classroom is a pedagogical approach that moves course content from the classroom to homework, and uses class time for engaging activities and instructor-guided problem solving. The course content in a sophomore level Organic Chemistry I course was assigned as homework using video lectures, followed by a short online quiz. In class, students’ misconceptions were addressed, the concepts from the video lectures were applied to problems, and students were challenged to think beyond given examples. Students showed increased comprehension of the material and appeared to improve their performance on summative assessments (exams). Students reported feeling more comfortable with the subject of organic chemistry, and became noticeably passionate about the subject. In addition to being an effective tool for teaching Organic Chemistry I at a small college, flipping the organic chemistry classroom may help students take more ownership of their learning.
Introduction The first generation of e-learning or Web-based learning programs focused on presenting physical classroom-based instructional content over the Internet. Furthermore, first-generation e-learning (digitally delivered learning) programs tended to be a repetition or compilation of online versions of classroom-based courses. The experience gained from the first-generation of e-learning, often riddled with long sequences of 'page-turner' content and point-and-click quizzes, is giving rise to the realization that a single mode of instructional delivery may not provide sufficient choices, engagement, social contact, relevance, and context needed to facilitate successful learning and performance. In the second wave of e-learning, increasing numbers of learning designers are experimenting with blended learning models that combine various delivery modes. Anecdotal evidence indicates that blended learning not only offers more choices but also is more effective. November -December 2003 Issue of Educational Technology, Volume 43, Number 6, Pages 51-54. This article has two objectives: 1. To provide a comprehensive view of blended learning and discuss possible dimensions and ingredients (learning delivery methods) of blended learning programs. 2. To provide a model to create the appropriate blend by ensuring that each ingredient, individually and collectively, adds to a meaningful learning experience. Badrul Khan's blended e-learning framework, referred to here as Khan's Octagonal Framework (see Figure 1) enables one to select appropriate ingredients (http://BooksToRead.com/framework). Khan's framework serves as a guide to plan, develop, deliver, manage, and evaluate blended learning programs. Organizations exploring strategies for effective learning and performance have to consider a variety of issues to ensure effective delivery of learning and thus a high return on investment. Figure 1. Khan's Octagonal Framework.
Construct definition, Object classification, Attribute classification, Rater identification, Scale formation, and Enumeration and reporting (C-OAR-SE) is proposed as a new procedure for the development of scales to measure marketing constructs. C-OAR-SE is based on content validity, established by expert agreement after pre-interviews with target raters. In C-OAR-SE, constructs are defined in terms of Object, Attribute, and Rater Entity. The Object classification and Attribute classification steps in C-OAR-SE produce a framework (six types of scales) indicating when to use single-item vs. multiple-item scales and, for multiple-item scales, when to use an index of essential items rather than selecting unidimensional items with a high coefficient alpha. The Rater Entity type largely determines reliability, which is a precision-of-score estimate for a particular application of the scale.
The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addition to the known problems related to sample size and power, is that it may indicate an increasing correspondence between the hypothesized model and the observed data as both the measurement properties and the relationship between constructs decline. Further, and contrary to common assertion, the risk of making a Type II error can be substantial even when the sample size is large. Moreover, the present testing methods are unable to assess a model's explanatory power. To overcome these problems, the authors develop and apply a testing system based on measures of shared variance within the structural model, measurement model, and overall model.
The general aim of the contributions to this special issue was to foster learning in computer supported collaborative learning environments by designing instructional interventions that enhance collaboration between learners. Scripts and external representations were used as instructional interventions to support social and cognitive processes, respectively, during collaborative learning. Although, the interventions enhanced these social and cognitive processes, beneficial effects on learning outcomes were not always found. This discussion uses cognitive load theory, particularly the expertise reversal effect, to explain these results. It is concluded that the principles from this theory which pertains to individual learning, show great promise for the design of collaborative learning environments.
Using Multivariate Statistics
- B G Tabachnick
- L S Fidell