Using Design-Based Research to Develop Meaningful Online Discussions in Undergraduate Field Experience Courses

We used the design-based research approach to test and refine a theoretically grounded goal-access-feedback-challenge-collaboration gamification model. The testbed was a 10-week, university-level e-learning design course offered in two consecutive semesters. In Study 1, we implemented the initial goal-access-feedback-challenge-collaboration model in semester one of the 2020–2021 academic year (N = 26). The aim was to enhance student behavioral engagement in online discussion forums, affective engagement in the class, and learning performance. The results of Study 1 showed that although most participants were engaged in this gamified learning experience during the first two sessions, they gradually lost interest and their participation in online discussions dropped over the next eight weeks. Thus, we introduced a new element, fantasy, into the original model. In Study 2, we tested the effectiveness of the goal-access-feedback-challenge-collaboration-fantasy model on students’ learning outcomes in semester two of 2020–2021 (N = 23). The results of Study 2 suggested that, compared to the original model, the goal-access-feedback-challenge-collaboration-fantasy model can better promote students’ engagement in online discussion, as measured by increased interaction with peers, learning experience, and learning performance.

BackgroundInvestigating emotion sequence patterns in the posts of discussion forums in massive open online courses (MOOCs) holds a vital role in shaping online interactions and impacting learning achievement. While the majority of research focuses on the relationship between emotions and interactions in MOOC forum discussions, research on identifying the crucial difference in emotion sequence patterns among different interaction groups remains in its infancy.ObjectivesThis research utilizes deep learning and sequential pattern mining to investigate whether there are differences in emotion sequence patterns across different groups of learners who exhibit various types of interactions in online discussion forums.MethodsData from a comprehensive array of sources, including log files, discussion texts and scores from 498 learners in online discussion forums, were collected for this study. The agglomerative hierarchical algorithm is used to classify learners into groups with different levels of interactions. Additionally, we implement and evaluate multiple deep learning models for detecting different emotions from online discussions. Relevant emotion sequence patterns were identified using sequence pattern analysis and the identified emotion sequence patterns were compared across different groups with different levels of interactions.Results and ConclusionsUsing an agglomerative hierarchical algorithm, we classified learners into three distinct groups characterized by different levels of interactions: high, average and low level. Leveraging the bi‐directional long short‐term memory model for emotion detection yielded the highest predictive performance, with an impressive F‐measure of 94.01%, a recall rate of 93.83% and an accuracy score of 95.01%. The results also revealed that learners in the low‐level interaction group experienced more emotion transition from boredom to frustration than the other two groups. Therefore, the aggregation of students into groups and the utilization of their MOOC log data offer educators the capability to provide adaptive emotional feedback, customize assessments and offer more personalized attention as needed.

The current study aimed at investigating the influence of classroom management on students’ engagement in learning and the moderating role of in-service training among selected Secondary schools in kumba 1 municipality. Specifically, it was purposed to find out the influence of exploratory teaching methods and students’ engagement in learning, to investigate how communication influences students’ engagement in learning, to determine the effect of reinforcement on students’ engagement in learning, to explore the influence of classroom environment on students’ engagement in learning and to examine the moderating role of in-service training in the relationship between classroom management and students’ engagement in learning. By use of a status cross-sectional quantitative research design, data for 132 secondary school students’ and 20 teachers in Kumba 1 municipality gathered using questionnaires. Data was analyzed using SPSS PROCESS macro. The results showed that exploratory teaching methods and classroom environment have significant positive influences on students’ engagement in learning. Thus, these findings emphasize the importance of learner-centered pedagogy and conducive classroom settings in promoting active learning. On the contrary, reinforcement and communication did not show statistically significant effects, although communication showed a near-significant positive trend. The findings further suggest that effective classroom management can substantially improve student engagement, particularly when mediated through continuous in-service training. Thus, comprehensive classroom management remain crucial for enhancing student engagement in learning.

The Independent Curriculum is an educational innovation providing flexibility for schools to design learning strategies suited to students’ characteristics. This study evaluates the effectiveness of implementing the Independent Curriculum using the Deep Learning approach at SD Negeri Cikampek Selatan I. The research employed a descriptive qualitative method through interviews, observations, and document analysis. Data were analyzed using an interactive model consisting of data reduction, presentation, and conclusion drawing. The findings show that applying deep learning principles enhances student engagement, independence, and critical thinking. Teachers have begun implementing conscious, meaningful, and joyful learning by integrating intellectual, emotional, aesthetic, and physical aspects. However, challenges remain in teacher readiness for new pedagogical practices and limited digital learning facilities. Recommendations emphasize strengthening teacher capacity in deep learning, fostering collaborative learning, and optimizing technology use to support meaningful and sustainable learning. Keywords: Independent Curriculum, Deep Learning, Student Engagement, Teacher Readiness, Meaningful Learning.

Undergraduate field experiences (UFEs) are key components of many biology, ecology, and geoscience programs and important steps to successful recruitment into careers. Through semistructured interviews of diverse field program leaders, we seek to understand how field program leaders conceptualize both their scientific disciplines and the intentional design factors they implemented within the UFE itself. Additionally, this study explores critical considerations these program leaders use to approach designing inclusive UFEs as well as the institutional and practical challenges of designing and implementing their UFEs. We acknowledge the limitations of the small sample of respondents, and our intent with this article is to explore these responses as a way to share critical design factors for designing and implementing inclusive UFEs with the broader geoscience community. Building an early understanding of these factors will help new field program leaders address multiple, simultaneous challenges that currently foment the underrepresentation of students from marginalized backgrounds in biology, ecology, and the geosciences. Through these explicit conversations, we hope to support the professional development of a scientific community that values the creation of safe, encouraging field experiences in which students can enhance their self-identity in the sciences, build peer and professional networks, and develop memorable field experiences that support their trajectories toward successful careers.

A discussion forum is a valuable tool to support student learning in online contexts. However, interactions in online discussion forums are sparse, leading to other issues such as low engagement and dropping out. Recent educational studies have examined the affordances of conversational agents (CA) powered by artificial intelligence (AI) to automatically support student participation in discussion forums. However, few studies have paid attention to the safety of CAs. This study aimed to address the safety challenges of CAs constructed with educational big data to support learning. Specifically, we proposed a safety‐aware CA model, benchmarked with two state‐of‐the‐art (SOTA) models, to support high school student learning in an online algebra learning platform. We applied automatic text analysis to evaluate the safety and socio‐emotional support levels of CA‐generated and human‐generated texts. A large dataset was used to train and evaluate the CA models, which consisted of all discussion post‐reply pairs ( n = 2,097,139) by 71,918 online math learners from 2015 to 2021. Results show that while SOTA models can generate supportive texts, their safety is compromised. Meanwhile, our proposed model can effectively enhance the safety of generated texts while providing comparable support. Practitioner notes What is already known about this topic Online discussion forums have been plagued by a lack of interaction among students due to factors such as expectations to receive no response and perceptions of topic irrelevance which lead to low motivation to participate. AI‐based conversational agents can automatically support students' interactions in online discussion forums at a large scale, and their generated responses can be human‐like, contextually coherent and socio‐emotionally supportive. Unsafe discourse exchanges between students and conversational agents can be dangerous as identity attacks, aggravation and bullying behaviours embedded in discourses can disrupt students' knowledge inquiry and negatively influence student motivation and engagement. However, few educational studies have paid attention to the safety of conversational agents. What this paper adds This study proposes and synthesized strategies to build AI‐based conversational agents that automatically support online discussions with safe and supportive discourses. This study reveals the relationship between discourse safety and social support, suggesting supportive discourses can also be unsafe. This study enriches the literature on educational conversational agents by synthesizing a conceptual framework on discourse safety and social support, and by proposing concrete algorithmic strategies to improve the safety of conversational agents. Implications for practice and/or policy Researchers and practitioners can adopt strategies in this study such as generation control, open‐sourced models and public API services to evaluate students' discourse safety for early intervention or modify existing conversational agents to be safety‐aware. Practitioners can utilize the proposed conversational agent to automatically support students both safely and socio‐emotionally at a large scale. Practitioners should be cautious when examining social support with automatic analysis, as not all supportive texts are safe. While unsafe texts can provide emotional support, it does not justify their appropriateness in a learning environment.

Effective online learning practices should incorporate an active social presence that provides space and technological support for students and instructors to engage in social activities, which are an integral part of the learning process. The focus of this chapter is the description of social presence, the forms in which it occurs, and how social presence enhances student engagement in the learning process, whether online or face-to-face. Based on various studies related to this topic, the authors argue that social presence has a significant impact on student engagement, especially in online classes. Finally, this chapter examines how social presence affects student engagement and offers various strategies for instructors to enhance social presence and student engagement in online learning.

Students' engagement in asynchronous online discussion: The relationship between cognitive presence, learner prominence, and academic performance

To explore the influence of the group personality composition on students' engagement in the online discussion, correlation analysis was conducted among the Big-5 personality of group members and student engagement in the group. This study comprehensively used four measurement indicators of the Big-Five personality of group members as group composition: average, variance, maximum, and minimum. In this study, student engagement was divided into behavioral engagement, affective engagement, and cognitive engagement. The study found that the combination of the Big-Five personalities in the group could have an impact on student engagement, especially affective engagement. When organizing students' online discussion, the instructors need to consider the personality characteristics of the group members carefully.

This experimental study investigates the effectiveness of virtual experiential learning in fostering student engagement by comparing the engagement and learning outcomes of two groups of students. One group (n = 69) participated in a virtual field trip to a winery, while the other group (n = 36) completed the field trip in person as part of an undergraduate culinary tourism course. A mixed-method approach was used to collect and triangulate data from a student engagement survey, reflective diaries, and assessment marks, which were analyzed using T-test and ANOVA, thematic analysis and descriptive statistics, respectively. Results showed that experiential learning increased students’ skill and emotional engagement in both groups while having no impact on participation and performance engagement. Skill engagement was significantly higher in the virtual group, while the in-person group scored slightly higher in emotional and performance engagement. Deep learning, however, was only reported by students who completed the in-person field trip.

The increasing use of online discussion forum (ODF) as an online computer-mediated communication (CMC) system that allows students to construct knowledge, collaborate and engage with new knowledge has resulted in a growing body of research that aimed at finding ways to enhance student learning outcomes using this platform. After an intensive web search was conducted using Google Scholar, seven previous systematic reviews that studied research trends in ODF were found. These studies have conducted systematic reviews on many different trends, factors and conditions to enhance student learning outcomes in ODF. The aim of the present study was to gather, analyze, and synthesize the seven previous systematic reviews in identifying holistic trends, factors, and conditions that have been reviewed and reported by them towards understanding the successful enhancement of student learning outcomes in this platform. The potential combinations of trends, factors, and conditions that emerged from the syntheses can act as a more holistic predetermined trends, factors and conditions for future improvement on the systematic review research. This study identified and categorized the trends, factors and conditions emerged under three different categories (i.e. general current trends, factors influencing ODF learning outcome (independent variables), and the achievement of ODF learning outcomes (dependent variables)). First and foremost, this study found that the general current trends reported on the ODF research area were based on the research site by region, academic context and academic discipline, forum platform, number of papers per year and research papers per journal, research design, type of analysis, and analysis framework. Next, in terms of the factors and conditions influencing the learning outcome of ODF, previous systematic reviews have reported their findings in terms of (i) stating the purpose in learning activity in ODF, (ii) protocol used in ODF, (iii) pedagogical strategies used in ODF, (iv) assessment used in ODF, (v) moderation used in ODF, (vi) student characteristics in ODF, and (vii) technology issues in ODF. Finally, in terms of the factors and conditions influencing the achievement of ODF learning outcome, they have reported their findings in terms of (i) thinking skills, (ii) achievement, (iii) social construction of knowledge, (iv) communication skills, and (v) others. The findings can help guide novice researchers in finding research gap from previous ODF studies and create opportunity that include forming an important reference base for a more holistic future systematic review in ODF field.

Background. A leading concern in teaching and learning is how to increase the degree of student engagement in learning. Within the virtual educational environment, student engagement is a real issue facing instructors and teachers. Students in online classrooms are not able to engage in the same manner as in face-to-face settings. Purpose. This study aims to explore the impact and reception of online education on student engagement in English as a foreign language (EFL) classroom. Method. This study adopts a mixed-method approach, in order to understand student engagement online. Longitudinal self-report surveys (SRS) filled out by 127 undergraduate students after each class session throughout a four-week period were used to assess their engagement in online language classrooms. Focus-group interview transcriptions were used to triangulate the data and provide further information about student engagement in terms of gender difference, engagement growth over time, and engagement fostering or hindrance factors in virtual learning classrooms. Results. Analysis showed that students were generally engaged during the weeks with some variances. Cognitive-social learning engagement showed dynamics among students in virtual language classrooms. Factors such as place of engagement and students’ choice of device used to access the virtual session were found to influence student engagement in online classroom learning. Male and female students generally showed similar learning engagement in the virtual classes with disparities occurring over the study period. Conclusion. The study results will be beneficial for researchers, instructors, and policymakers who are interested in understanding student engagement and who seek to improve the teaching experience.

BackgroundHuman genomics research is growing rapidly. More effective methods are required for co-design and involving people, especially those sub-populations which are inherently high interest to medical research and thus at greater risk of being exploited. This case study documents how we worked with a large group of donor-conceived siblings who share the same sperm donor father, to explore how they might want to engage with and influence any future genomic research.MethodA participatory action research process was used to explore the views of a group of 18 people who knew they are donor-conceived siblings. They are part of a larger group of up to 1000 people who share the same sperm donor father but the only ones in contact with each other; it is likely that many of the uncontacted siblings are unaware of their biological father, have been unable to trace others or have died. The discussion explored views about how the group would like to be involved in future research. Five members participated in co-design; 12 completed a pre-discussion online survey; and six participated in an online discussion forum and evaluation survey. The online discussion was led by one facilitator, supported by the study team.ResultsOf the 18 siblings approached in 2018, 14 participated in the co-design stages or the surveys and online discussion. Co-design informed the research process. Participants reported enjoying the overall experience of the surveys and discussion forum, which were perceived as inclusive and flexible. Most participants’ views regarding the value of involvement in research changed during the process, and ‘widened’ about who should be involved. Participants were supportive of future research being done with the siblings group. All who completed the final survey requested to remain part of the co-design process. Other themes in the online discussion included concerns about conflicting interests and a desire for research participation to improve the situation for people affected by assisted conception. The process informed later discussions in the sibling group about participating in a self-managed biobank and informed decision making about participating in genomics research.ConclusionFindings from this study help inform ways in which people from certain sub-populations can be involved in planning and defining their participation in genomic research, particularly those that are inherently high interest to medical research and thus at greater risk of exploitation. This process provides a replicable method of involving potential participants in co-designing genomics research using online discussions, with positive outcomes. Reporting this study using ‘Standardised data on initiatives (STARDIT)’ to report the process allows comparison with other studies.

Learning through the Lounge: Using Social Presence to assess the learning environment in a MyLinE online forum

As the main driver of talent cultivation in colleges and universities, the learning and development level of college students is a core indicator of the quality of talent cultivation. The current status of college students' learning has always been a heavily researched topic. However, there is a lack of academic research on the potential mechanisms of self-control about how it affects college students' learning engagement. This study explored the relationship between college students' self-control and learning engagement and the potential mechanisms underlying this relationship with reference to a large sample. A total of 765 college students from Guangxi, China, completed the self-control scale, the resilience scale, the positive emotions scale, and the learning engagement scale. SPSS 26.0 was used to conduct common method bias tests, descriptive statistics, correlation tests, and regression analyses. Structural equation modeling was constructed using AMOS 26.0, and mediation effects were tested. This article mainly used questionnaires to collect data and, on this basis, examined the relationship between self-control, resilience, positive emotions, and the learning engagement of college students. The results showed that (1) self-control positively affected college students' learning engagement; (2) resilience partially mediated the relationship between self-control and college students' learning engagement; (3) positive emotions partially mediated the relationship between self-control and college students' learning engagement; and (4) resilience and positive emotions played a chain-mediating role between self-control and college students' learning engagement. The present study identifies the potential mechanism underlying the association between the self-control and learning engagement of college students. The results of this study have practical implications for enhancing the learning engagement of Chinese college students by increasing their psychological resources and improving the teaching of university teachers.