Student-to-student connectedness is promoted by active, student-centered learning processes. It is a socio-psychological result of interpersonal communication and behavior in the classroom, which emulates belonging, cohesiveness, and supportiveness among peers. Currently, two survey instruments exist—Dwyer et al.’s (Commun Res Rep 21(3):264–272, 2004. https://doi.org/10.1080/08824090409359988) Connected Classroom Climate Inventory and Johnson’s (Commun Res Rep 26(2):146–157, 2009. https://doi.org/10.1080/08824090902861622) amendment thereof, which have been used for nearly two decades to gain insight into instructional processes in face-to-face environments. However, research on student-to-student connectedness is relatively limited in the context of modern, technology-mediated learning environments. Arguably, where student-to-student connectedness is most urgently needed because of the decrease in face-to-face contact time between students and their instructors within online and hybrid learning environments. This study is a systematic literature review that presents a synthesis of twenty-four peer-reviewed journal articles, which empirically investigate student-to-student connectedness within face-to-face, hybrid, and online environments. The documentation of data is organized in accordance to the six aspects of activity theory (subjects, objects, mediating artifacts, rules, community, division of labor) to provide a basis for understanding the dynamics of each research report, as well as to assist identifying the trends and gaps in the literature, thereby expediting future research on this topic.
Journal of Computing in Higher Education
In educational psychology, the theories of interest and self-determination have been well studied to find the relationships between learning attitudes and learning outcomes. However, the instructional design and the learning behaviors are the two missing elements which have not been fully investigated in the learning process. Therefore, we conducted two studies longitudinally with 2 years data from a 13-week engineering course at the City University of Hong Kong in a blended learning environment to verify the criticalness of these elements in these studies. With engagement records being collected from the learning management system in the second year, we further correlated the relationship from situational interest to engaged learning and finally the academic performance. Our findings make theoretical contributions by combining these two theories and link the model with behavior and achievement of students. It also demonstrates the importance of these theories on the instructional design.
Evaluation of mobile learning for the clinical practicum in nursing education: application of the FRAME model
This paper presents an evaluation of mobile learning practice for the clinical practicum in nursing education. Nursing students need to practise nursing skills and follow specific clinical procedures in wards. In this study, they were provided with a mobile device for learning purposes, with mobile apps preinstalled for watching nursing videos and conducting clinical assessments. The evaluation was conducted following the Framework for the Rational Analysis of Mobile Education (FRAME). It included a questionnaire survey involving 265 nursing students and focus group interviews with 20 nursing students, the course coordinator of the clinical practicum and the instructional designer of the mobile apps. The participants shared their views, perceptions and experiences of mobile learning for studying nursing skills and conducting clinical assessment in the practicum context. The results showed the participants’ overall satisfaction with the mobile learning practice. They gave positive feedback on the use of the mobile apps in terms of enabling ubiquitous access to materials for situated learning in wards, and offering effective support for teachers to keep track of students’ learning progress. They also suggested areas for improvements, which emphasised the hardware capacity of devices, training on the use of apps and institutional support for the maintenance of devices. The results of factor analysis showed a composition of underlying factors different from that of the original FRAME model, which suggests contextual variation in the application of the model.
The application of online authentic language data has played an increasingly important role in language teaching. These include freely available online corpora such as the British National Corpus and the Corpus of Contemporary American English. However, students are easily overwhelmed by the enormous amount of incomplete sentences (concordance lines) contained therein and therefore may fail to consult keywords and expressions as a resource tool. As an alternative resource a new web-based platform for English language learning, called Sketch Engine for Language Learning (SkELL), has been developed. Unlike the aforementioned corpora, SkELL generates sufficient amount of complete sentences which help students learn multiple examples of lexical and grammatical items in context. However, little research has been conducted as to how Japanese students with lower English proficiency assess the efficacy of SkELL. This study aims to examine the potential and limitation of SkELL in the language classroom for Japanese students who have almost no online experience in educational settings. The findings indicate that there is a close relationship between students’ view of the utilisation and efficacy of the resource and their attitudes toward English education. The study concludes with a discussion of pedagogical implications of the use of SkELL as a valuable educational tool for students who are accustomed to traditional English language learning.
It is widely acknowledged that the acquisition of vocabulary is the foundation of learning English. With the rapid development of information technologies in recent years, e-learning systems have been widely adopted for English as a Second Language (ESL) Learning. However, a limitation of conventional word learning systems is that the prior vocabulary knowledge of learners is not well captured. Understanding the prior knowledge of learners plays a key role in providing personalized learning, which many studies suggest is a successful learning paradigm for vocabulary acquisition, one that aims to optimize instructional approaches and paces by catering to individual learning needs. A powerful learner profile model which can represent learner’s prior knowledge is therefore important for word learning systems to better facilitate personalized learning. In this article, we investigated various methods to establish learner profiles and attempted to determine the optimal method. To verify the effectiveness of personalized word learning supported by the proposed model, ESL students from several universities participated in this study. The empirical results showed that the proposed learner profile model can better facilitate vocabulary acquisition compared with other baseline methods.
Flipped Classroom (FC) is a blended learning approach being promoted in higher education in recent years. It flips the conventional pedagogic arrangement so that students use the out-of-class time to conduct lower-order learning and the in-class time to conduct higher-order learning. Nevertheless, unlike the adoption phenomena in other academic disciplines such as Science, Engineering, Medicine and Education in university teaching, the adoption of FC in Social Science has been rare. This paper reports on a quantitative study (n = 152) in which the Stages of Concern model was employed to probe into the concerns of Social Science faculty members (SSFMs) about introducing FC into their teaching practice. The study reveals that the participants were having strong categorical concerns of “Information” and “Management.” The findings shed light on designing more precise interventions for addressing SSFMs’ actual needs when flipping their classrooms, providing a useful reference for researchers and practitioners who are pursuing work on promoting FC in higher education.
Blended approach to learning and practising English grammar with technical and foreign language university students: comparative study
Blended design of teaching/learning foreign languages, in this case English grammar, has become widely spread within the higher education. The main objective of the article is to discover whether blended approach enhances the process of acquiring new knowledge in the field. The research was conducted at two institutions: faculty of informatics and management, University of Hradec Kralove (technical students) and faculty of education, University of Jan Evangelista Purkyne, Usti nad Labem (foreign language students), Czech Republic. Totally, the research sample included 123 bachelor students. Data were collected in three phases: (1) face-to-face pre-testing to monitor entrance knowledge before the process of blended learning starts, (2) post-testing 1 applied after the blended learning approach and (3) final face-to-face post-testing 2 administered at the end of semester. Phase 1 was followed by autonomous learning from the online course; teacher´s feedback was provided to the students after phase 2 so that they could correct their mistakes, and improve the knowledge in phase 3. Eight hypotheses were tested to discover whether there exist statistically significant differences in test scores between the technical and foreign language students. The results differ according to the students´ level of English knowledge. However, they entitle the described blended learning approach to be applied for acquiring English grammar for B2 and C1 levels of CEFR.
Exploring the difficulty on students’ preparation and the effective instruction in the flipped classroom
This study aims to find out how students prepared for a flipped classroom and to examine what type of instruction could effectively guide students to do pre-class preparation. We conducted case studies for over two years in a physiology class at a Japanese university. In a survey performed in 2017, students were asked to participate in a questionnaire and an interview. Their responses in the questionnaire indicated that there was a clear and positive correlation between their class preparation time and individual grades, while class preparation of some students was proven not so productive or efficient. By the same token, the student interview made clear that students were not well informed of what to focus on or how to prepare appropriately for the flipped classes. Based on the 2017 findings, we started to share learning objectives with students for their pre-class preparation in the 2018 course. Amid and after the 2018 spring semester, questionnaires were administered to examine the effectiveness of instructions for preparation, and of sharing learning objectives to measure the level of students’ metacognition. As a result, the students who continuously review the learning objectives achieved significantly higher grades than the students who did not. We also found that the level of students’ metacognition exerted a stronger influence on their grades than the amount of effort invested in reviewing the learning objectives for pre-class preparation. In conclusion, our study suggests that instructors should design a comprehensive flipped class model which maximizes the benefit of pre-class preparation time by envisioning that students’ preparation would be more sustainable and effective with proper guidance.
The use of an extended flipped classroom model in improving students’ learning in an undergraduate course
One of the biggest barriers preventing teachers from utilizing the flipped classroom approach in their teaching practices is the lack of a general and practical framework for guiding the design and implementation of flipped classrooms. This leads to the fact that the effectiveness of the flipped classroom approach is unconfirmed. Building on research findings from the field of learning and instruction, this study proposed a step-by-step general model named the “O-PIRTAS” (Objective, Preparation, Instructional video, Review, Test, Activity, Summary) flipped classroom model and examined its effectiveness in promoting student learning in an undergraduate psychology course. Two classes of 101 first-year undergraduates were taught by the flipped classroom model or the traditional lecture-based approach for 16 weeks. The results supported the effectiveness of the flipped classroom model; the flipped model not only improved the students’ perceptions of the teaching quality and peer interaction engagement but also promoted their generic skills development and examination performance. Instructional implications for implementing flipped instruction are provided, and directions for future research are discussed.
The paper proposes an interactive student response portfolio (ISREP) system with iBeacon and web-socket technology, which supports flipped-classroom learning activities in traditional classrooms. The design of the ISREP system aims at promote interactions in classroom learning (CL). It offers APPs and web-interface functions for students and teachers, respectively. Students’ APP can scan iBeacon devices in classrooms and then automatically upload their identification information to the cloud space. Consequently, students’ presence in classroom can be recorded automatically. Moreover, teachers employ another function the system provides to promote high interaction in classroom via displaying questions on the front screen in classroom. Meanwhile, it simultaneously pushes (multicasts) these questions to students’ smartphones via web-socket technology. Subsequently, students send their responses for questions to the cloud space by the APP. During answering questions, the system presents temporary histograms of students’ responses and counting-down statuses of a timer on the screen in classroom. A timer can be synchronized with students’ APP by the web-socket technology. This way can promote students’ interaction and interest and then students enjoy in quiz-like activities. Teachers can quickly get results of students’ responses. A quasi-experiment was conducted in flipped-CL activities of a university class utilizing the system. Observing experimental results, it was found that students, who receive the instruction with the system, improved their interaction, learning interest, learning attitude, and learning satisfaction. Moreover, the proposed system helps teachers quickly obtain students’ learning situation in classroom and then may adjust their instructional approaches or contents.
The flipped classroom gives students the flexibility to organize their learning, while teachers can monitor their progress analyzing their online activity. In massive courses where there are a variety of activities, automated analysis techniques are required in order to process the large volume of information that is generated, to help teachers take timely and appropriate actions. In these scenarios, it is convenient to classify students into a small number of groups that can receive dedicated support. Using only online activity to group students has proven to be insufficient to characterize relevant groups, because of that this study proposes to understand differences in online activity using differences in course status and learning experience, using data from a programming course (n = 409). The model built shows that learning experience can be categorized in three groups, each with different academic performance and distinct online activity. The relationship between groups and online activity allowed us to build classifiers to detect students who are at risk of failing the course (AUC = 0.84) or need special support (AUC = 0.73), providing teachers with a useful mechanism for predicting and improving student outcomes.
High levels of digital media use have become a feature of university lectures. While certainly capable of supporting learning outcomes, studies indicate that, when media use is off-task, it presents as a disruption, distracting both users and those around them from academic tasks. In this study an exploratory, mixed-methods assessment of a media use policy for a semester-long course is presented. This policy divided the lecture theatre into two sections, one for those who wished to use digital devices and one for those who did not. Such a policy empowered students to leverage the value of media, if desired, while affording those who wished not to use media, or be disrupted by their peers’ use of media, a degree of protection from distracting cues. Findings indicate that those who consistently selected the same side performed better than those who moved from side to side. Two post-course focus groups revealed that, while having some limitations, the policy was well received by the participants and heightened their awareness of the possible distractions of off-task media use, enabling them to identify and maintain a strategy for their in-lecture attentional allocation and behaviour.
Studies on engagement and learning design in Massive Open Online Courses (MOOCs) have laid the groundwork for understanding how people learn in this relatively new type of informal learning environment. To advance our understanding of how people learn in MOOCs, we investigate the intersection between learning design and the temporal process of engagement in the course. This study investigates the detailed processes of engagement using educational process mining in a FutureLearn science course (N = 2086 learners) and applying an established taxonomy of learning design to classify learning activities. The analyses were performed on three groups of learners categorised based upon their clicking behaviour. The process-mining results show at least one dominant pathway in each of the three groups, though multiple popular additional pathways were identified within each group. All three groups remained interested and engaged in the various learning and assessment activities. The findings from this study suggest that in the analysis of voluminous MOOC data there is value in first clustering learners and then investigating detailed progressions within each cluster that take the order and type of learning activities into account. The approach is promising because it provides insight into variation in behavioural sequences based on learners’ intentions for earning a course certificate. These insights can inform the targeting of analytics-based interventions to support learners and inform MOOC designers about adapting learning activities to different groups of learners based on their goals.
E-learning assessment for tourism education LISREL assisted intercultural tourism perception and data integrated satisfaction perspectives
With the intensification of global integration, education internationalization has become one of the important indicators for evaluating the level of higher education development in a country. From the total income of tourism in recent years and its contribution to China’s GNP, it can be seen that the tourism industry has a strong development momentum. Tourism culture has become a mobile culture of which essence is cross-cultural tourism. Therefore, studying tourism from an intercultural perspective is an inevitable trend under the globalization of international tourism. Meanwhile, the contribution of tourism education talents is an important guarantee for the sustainable development of tourism. The dominant growth of the tourism industry has undoubtedly promoted the in-depth development of tourism education. Therefore, the development of tourism education and tourism industry should be a dynamic development pattern which promotes each other. This article regards the relationship between perception and satisfaction as the starting point and introduces the LISREL model into cross-cultural tourism research. This paper constructs a cross-cultural tourism research model and studies the relationship between perception and satisfaction, which can also be used to study other aspects of cross-cultural tourism.
Digital badges (i.e., digital credentials for achievements) have been suggested as a useful and scalable implementation of gamification. Digital badges (hereafter “badges”) provide two potential supports for learning: (1) badges provide support for motivation by rewarding achievement and (2) badges provide implicit learning goals. The present paper describes two experiments in which we investigated whether badges can support self-regulated learning by comparing their impact on learning with students given explicit goals for student learning, a key factor in self-regulated learning. Specifically, we compared the effects of badges and goal setting in a low-stakes learning context (Experiment 1; online extra credit unit) and a high-stakes learning context (Experiment 2; introductory Educational Psychology courses). In these two quasi-experiments, participants were randomly assigned to one of four groups: badge only, goal only, badge + goal, or control (i.e., no badge, no goal). Learning was measured by comparing performance on topics related to Turkish Culture (Experiment 1) or Educational Psychology (Experiment 2) at pre-test and post-test. Somewhat surprisingly, the results from both studies demonstrated no significant improvement in learning between groups. The discussion suggests that caution should be taken when incorporating badges in learning contexts and provides guidance on the conditions under which badges may be most effective for supporting learning.
A supervised learning framework: using assessment to identify students at risk of dropping out of a MOOC
Both educational data mining and learning analytics aim to understand learners and optimise learning processes of educational settings like Moodle, a learning management system (LMS). Analytics in an LMS covers many different aspects: finding students at risk of abandoning a course or identifying students with difficulties before the assessments. Thus, there are multiple prediction models that can be explored. The prediction models can target at the course also. For instance, will this activity assessment engage learners? To ease the evaluation and usage of prediction models in Moodle, we abstract out the most relevant elements of prediction models and develop an analytics framework for Moodle. Apart from the software framework, we also present a case study model which uses variables based on assessments to predict students at risk of dropping out of a massive open online course that has been offered eight times from 2013 to 2018, including a total of 46,895 students. A neural network is trained with data from past courses and the framework generates insights about students at risk in ongoing courses. Predictions are then generated after the first, the second, and the third quarters of the course. The average accuracy that we achieve is 88.81% with a 0.9337 F1 score and a 73.12% of the area under the ROC curve.
Preservice teachers’ Web 2.0 experiences and perceptions on Web 2.0 as a personal learning environment
To explore students’ use of Web 2.0 tools and their perceptions of using Web 2.0 as a personal learning environment (PLE), quantitative surveys (n = 113) and interviews (n = 12) were conducted. In the survey, we identified that students already have familiarity with using Web 2.0 tools, as well as a positive attitude toward using Web 2.0 for learning. However, in the interview, students referenced challenges with using Web 2.0 in their PLE. The results imply that there are gaps between students’ perceived comfort and familiarity with using Web 2.0 tools and their readiness to be an active and successful designer for Web 2.0-based PLEs. This research also identified that there may be other factors influencing students’ building PLEs with Web 2.0 tools including the knowledge of different tools, the abilities of identifying learning objectives and learning styles, access to the tools, motivation, and knowing how to locate the correct information through students’ interviews.
Content assessment has broadly improved in e-learning scenarios in recent decades. However, the e-Learning process can give rise to a spatial and temporal gap that poses interesting challenges for assessment of not only content, but also students’ acquisition of core skills such as self-regulated learning. Our objective was to discover students’ self-regulated learning processes during an e-Learning course by using Process Mining Techniques. We applied a new algorithm in the educational domain called Inductive Miner over the interaction traces from 101 university students in a course given over one semester on the Moodle 2.0 platform. Data was extracted from the platform’s event logs with 21,629 traces in order to discover students’ self-regulation models that contribute to improving the instructional process. The Inductive Miner algorithm discovered optimal models in terms of fitness for both Pass and Fail students in this dataset, as well as models at a certain level of granularity that can be interpreted in educational terms, which are the most important achievement in model discovery. We can conclude that although students who passed did not follow the instructors’ suggestions exactly, they did follow the logic of a successful self-regulated learning process as opposed to their failing classmates. The Process Mining models also allow us to examine which specific actions the students performed, and it was particularly interesting to see a high presence of actions related to forum-supported collaborative learning in the Pass group and an absence of those in the Fail group.
How do people come to think of themselves as instructional designers? This is partly a matter of acquiring expertise, e.g., the knowledge and skill sets found in professional standards, e.g., those of IBSTPI or AECT. But identity also involves adoption of new professional roles and affiliation and active engagement with professional communities. IDT academic programs facilitate and sport student in their induction into the field, but not always in a systematic, intentional way. Indeed in today’s world, IDT professionals may identify with different fields and roles depending on situation and context. This article explores these issues and provides a conceptual framework for understanding how people take on new IDT identities and the role played by academic programs in that process. The framework consists of a set of guiding principles and processes, A set of recommendations is then offered for IDT academic programs to begin seeing professional identity as a learning outcome and supporting students along that important journey.