Student wellbeing

Workload and Wellbeing: Striking a Delicate Balance for Academic Success in Blended Learning

cdtlsd Paper Presentations , , , ,

Jodie LUU*, Brenda YUEN Pui Lam, Marissa E Kwan Lin, and Misty So-Sum WAI-COOK 

Centre for English Language Communication (CELC), NUS 

*jodieluu@nus.edu.sg 

Luu, T. H. L., Yuen, B. P. L., E, M. K. L., & Wai-Cook, M. S. S. (2024). Workload and wellbeing: Striking a delicate balance for academic success in blended learning [Paper presentation]. In Higher Education Conference in Singapore (HECS) 2024, 3 December, National University of Singapore. https://blog.nus.edu.sg/hecs/hecs2024-jluu-et-al/

SUB-THEME

Opportunities from Wellbeing

KEYWORDS

perceived workload, blended learning pedagogy, student wellbeing, academic support 

CATEGORY

Paper Presentation 

EXTENDED ABSTRACT

Student wellbeing has always been a key consideration of teaching and learning. As a multi-dimensional construct, student wellbeing can be understood as “subjective, emotional and cognitive evaluations of school reality” that is “in favour of positive aspects” (Harsche, 2003, p. 129) of such reality. Growing empirical research has highlighted psychological and emotional distress, depression, and an increased risk of burnout as common wellbeing issues faced by university students (Backhaus et al., 2020; Baik et al., 2019; Larcombe et al., 2016). In Singapore, a mental health survey with undergraduates from five autonomous universities also found that work/study commitments were the top source of stress (89%) (Lim, 2022). Such findings point to workload as a potential factor worth examining given its integral role in curriculum design.  

 

Furthermore, the adoption of blended learning pedagogy to promote active learning in higher education presents students with a different teaching and learning environment that requires more adaptation by students. In theory, a well-calibrated flow between in-person and online activities is desirable to manage the workload for both students and faculty (McGee & Reis, 2012). In practice, while some students may enjoy the flexibility to engage with online learning materials at their own pace (Phillips et al., 2016), others may perceive an increased workload resulting from the lack of work-life balance, amount of assignments, and connectivity/technical issues with devices (Hilliger et al., 2023). This mixed perception of workload in relation to blended learning pedagogy raises a noteworthy question of how to strike a delicate balance between ensuring the academic rigor of the curriculum and offering appropriate academic support without jeopardising student learning. 

 

According to Kyndt et al. (2013), workload has both objective and subjective (or perceived) dimensions. While the former is usually set based on the expected number of hours spent on various course components, the latter is more complex. Defined as “a combination of the demands placed upon the student, and the effect of these demands on the student, such as effort and frustration” (Kyndt et al., 2013, p. 685), perceived workload consists of both quantitative elements such as time and amount of work and qualitative elements such as the nature of assessment, teaching and learning environment, and learners’ personal characteristics. The interplays of these elements may influence how students view their academic workload, which in turn affect their wellbeing. 

 

In this light, this study aims to examine students’ perception of the workload in various blended learning courses offered by the Centre for English Language Communication (CELC) at NUS. A survey questionnaire was administered with students taking 12 CELC courses in Semester 1 of AY2023/24. The quantitative analysis of the six 4-point Likert scale statements (1=Should be implemented but missing to 4=Excellent implementation) related to workload showed a mean score of 3.26 (S.D.=0.66) among 299 students. This suggests that most respondents showed positive perception of workload as the blended course courses demonstrated an appropriate balance of online and in-class learning activities. Furthermore, preliminary sentiment analysis of responses to the open-ended question on students’ attitude about blended learning shows positive sentiment associated with themes such as learning, experience, environment, and practice. These themes echo the teaching and learning environment dimensions of Kyndt et al.’s (2013) conception of perceived workload. Combining these results with insights from follow-up interviews with students who shared about strategies to navigate their study commitments, we argue that a more holistic view of workload that encompasses both quantitative and qualitative perceived dimensions should be adopted in blended learning curriculum design. In so doing, educators would be able to implement appropriate academic support that strikes a delicate balance between academic success and mental wellbeing.

REFERENCES

Backhaus, I., Varela, A. R., Khoo, S., Siefken, K., Crozier, A., Begotaraj, E., Fischer, F., Wiehn, J., Lanning, B., Lin, P., Jan, S., Zaranza Monteiro, L., Al-Shamli, A., La Torre, G., & Kawachi, I. (2020). Associations between social capital and depressive symptoms among college students in 12 countries: Results of a cross-national study. Frontiers in Psychology, 11, 644. https://doi.org/10.3389/fpsyg.2020.00644  

Baik, C., Larcombe, W., & Brooker, A. (2019). How universities can enhance student mental wellbeing: The student perspective. Higher Education Research & Development, 38(4), 674–687. https://doi.org/10.1080/07294360.2019.1576596 

Hascher, T. (2003). Well-being in school—why students need social support. In P. Mayring & C. von Rho ¨neck (Eds.), Learning emotions—the influence of affective factors on classroom learning (pp. 127–142). Bern u.a Lang. 

Hilliger, I., Astudillo, G., & Baier, J. (2023). Lacking time: A case study of student and faculty perceptions of academic workload in the COVID‐19 pandemic. Journal of Engineering Education, 112(3), 796–815. https://doi.org/10.1002/jee.20525 

Kyndt, E., Berghmans, I., Dochy, F., & Bulckens, L. (2013). ‘Time is not enough.’ Workload in higher education: a student perspective. Higher Education Research and Development, 33(4), 684–698. https://doi.org/10.1080/07294360.2013.863839   

Larcombe, W., Finch, S., Sore, R., Murray, C. M., Kentish, S., Mulder, R. A., Williams, D. (2016). Prevalence and socio-demographic correlates of psychological distress among students at an Australian university. Studies in Higher Education, 41, 1074–1091. https://doi.org/10.1080/03075079.2014.966072

Lim, K. (2022, June 21). Large-scale survey of Singapore undergrads finds work and study commitments as main stressors, desire for academic “grace days.” TODAY. https://www.todayonline.com/singapore/survey-singapore-undergrads-work-study-stress-academic-grace-days-1929776  

McGee, P., & Reis, A. (2012). Blended course design: A synthesis of best practices. Journal of Asynchronous Learning Networks, 16(4), 7–22. https://doi.org/10.24059/olj.v16i4.239 

Phillips, J. A., Schumacher, C., & Arif, S. (2016). Time spent, workload, and student and faculty perceptions in a blended learning environment. American Journal of Pharmaceutical Education, 80(6), 1–9. https://doi.org/10.5688/ajpe806102  ​ 

Powering Peer Support

cdtlsd Lighting Talks , , , , ,

Melissa ZEHNDER and Duane ONG

Singapore Institute of Technology (SIT) 

melissa.zehnder@singaporetech.edu.sg, duane.ong@singaporetech.edu.sg

Zehnder, M., & Ong, D. (2024). Powering peer support [Lightning talk]. In Higher Education Conference in Singapore (HECS) 2024, 3 December, National University of Singapore. https://blog.nus.edu.sg/hecs/hecs2024-mzehnder-dong/

SUB-THEME

Opportunities from Wellbeing

KEYWORDS

Opportunities from Wellbeing, student peer support, wellbeing, student wellbeing, mental health, student engagement

CATEGORY

Lightning Talk

EXTENDED ABSTRACT

Students in university experience significant stress, they have to navigate and adapt to new environments and adopt new behaviours. At the Singapore Institute of Technology (SIT), we aim to provide holistic and extensive student care and support. To this end, a Student Development and Care Strategy has been established to ensure a safe, vibrant and supportive campus community. This framework encompasses aspects of student development, integration, care and recreation, to boost their learning journey beyond academic rigour. Throughout each academic year, there is continuous student engagement and support. This creates a common campus vocabulary on good mental health habits and normalises help-seeking behaviours. Often, this is accomplished by harnessing the power of peer-to-peer support. 

 

In 2022, SIT embarked on a peer-to-peer emotional support programme. Potential supporters were interviewed for the programme, before they embarked on specially curated training with five core modules. To help drive ground-up initiatives, a student executive committee was installed. As a group, these peer supporters engage the student community to promote available support (theirs included) and resources for good mental health. Some challenges faced include lack of student awareness of the presence of peer support and their willingness and knowledge of how to connect with a peer supporter, as well as understanding the benefits of peer support. 

 

The next phase of the peer support service has begun, where the student peer supporters should be gainfully engaged and students seeking the support report reaping benefits. 

 

Feedback from other stakeholders such as SIT faculty will also be consolidated. The presentation will share a summary of the Student Development and Care Strategy, objectives of the SIT peer support programme, challenges faced and ideas to navigate these challenges, success stories, as well as ideas for the future. If possible, the presentation will have both SIT staff and student peer supporters sharing their peer support experiences. 

 

Student Wellbeing: Perception of Support in Blended Learning Environments

cdtlsd Paper Presentations , , , ,

*Netty Haiffaq Binte Zaini MATTAR, Aileen Wanli LAM, and Doreen TAN 

Centre for English Language Communication  (CELC), NUS

*nmattar@nus.edu.sg 

Netty Haiffaq Zaini Mattar, Lam, A. W. L., & Tan, D. (2024). Student wellbeing: Perception of support in blended learning environments [Paper presentation]. In Higher Education Conference in Singapore (HECS) 2024, 3 December, National University of Singapore. https://blog.nus.edu.sg/hecs/hecs2024-nmattar-et-al/

SUB-THEME

Opportunities from Wellbeing 

KEYWORDS

Blended learning, system-level support, student perception, student wellbeing. 

CATEGORY

Paper Presentation

 

EXTENDED ABSTRACT

Blended learning is a potentially transformative approach to education that can result in personalized learning (Kumar et al, 2021) and increased efficiency (Dwiyogo, 2020), thus maximising learning potential (Poon, 2013) through the blending of content and technology (Liu et al., 2024). Blended learning involves various combinations of traditional face-to-face learning with online technologies. This means that students need to toggle between synchronous and asynchronous lectures, materials, activities, and tasks which can include retrieving and viewing content throughout the semester (e.g. readings and videos), collaboration on activities online (e.g. peer review and collaborative writing), and participation in formative and summative assessments on various online platforms. These platforms range from learning management systems like Canvas and Blackboard, collaborative tools like Google Drive and Microsoft Teams, video conferencing tools like Zoom, as well as interactive tools like Slido and Kahoot. Because of the multiple platforms and learning modes involved, students can feel disorientated, overwhelmed, and anxious (Allen & Seaman, 2013), especially if the information and procedures to access online components of the course is unclear or if students need to use sophisticated applications (Vaughan, 2007). This has a negative impact on students’ mental and emotional wellbeing, leading to symptoms like “stress, neck impairment and back disability” (Agarwal & Agarwal, 2022) as students navigate the challenges of blended learning environments (Conwi et al., 2024). When students are unfamiliar with platforms and systems (Kadaer et al., 2022), have not been prepared for the programme (Willging & Johnson, 2009), or feel they “waste time on technical issues” (Sazdovska-Pigulovska, 2021), it can trigger stress, leading to negative impact. One implication is that increased student agency in blended environments must be accompanied by clear expectations and explicit guidance (O’Brien & Freund, 2018) such as instructions on the “primary presentation of course content” (Garrison et al., 2000, p. 90), clear protocols when communicating online, as well as high accessibility of materials.   

   

According to scholars like Salmon (2003) and Moule (2006), clarity of expectations, explicit instruction and high accessibility all relate to initial, system-level support in higher education online learning environments. Support here includes facilitating students’ access to course notes, activities, materials, databases, or platforms, in complex blended learning environments (Salmon, 2003, p. 28; Moule, 2006, p. 377). It also includes clear expectations about how to proceed with, and complete, activities, as well as clear protocols for communication between students and instructors, and for how to obtain technical support. Support at this level aids learning, but is not central to the actual learning process (Moule, 2007, p. 42). However, as mentioned, system-level support is essential to mitigating the emotional and psychological difficulties in blended learning environments, and thus essential to student wellbeing (Lancaster, 2022, p. 48).   

    

We are interested in how students, from a range of undergraduate and postgraduate courses at the National University of Singapore (NUS), perceive this system-level support in their courses. More specifically, we are interested in what aspects they perceive to be important.   

  

We draw our findings from a survey conducted with students from twelve blended courses offered by the Centre for English Language and Communication (CELC), NUS. The quantitative survey items covered course design, delivery, student workload, student engagement, assessments, use of technology, training and support for students and communication and overfall perceptions of the course. Two open-ended questions were also included at the end of the survey, and a thematic analysis was carried out on the qualitative feedback. The questions were:   

  1. What are the strengths and areas for improvement in the blended learning arrangement in my CELC course?  
  2. Overall, how do you feel about being part of a blended learning environment as a student?   

   

Based on the findings, this paper will share aspects of system-level support students perceive as important to bolster their well-being in blended learning environments. We propose that effective support mechanisms—such as thoughtful organisation of resources, streamlining of platforms, and frequent and clear communication—will positively impact the emotional wellbeing of students. Additionally, this paper provides practical recommendations educators can adopt to improve support structures. 

 

REFERENCES

Agarwal, A., & Agarwal, D. (2022). Implication of online learning on the physical and mental well-being of students. International Journal of Research in Engineering and Innovation, 06(05), 366–369. https://doi.org/10.36037/IJREI.2022.6508  

Allen, I. E., & Seaman, J. (2013). Changing Course: Ten Years of Tracking Online Education in the United States. Sloan Consortium (NJ1). https://eric.ed.gov/?id=eD541571  

Conwi, C., Pinar, W., & Destura, M. (2024). Exploring mental wellbeing, distress and adjustment in a blended learning environment. Journal of Interdisciplinary Perspectives, 2(7), 146-157. https://doi.org/10.69569/jip.2024.0148  

Dwiyogo, W. D. (2020). Effectiveness, efficiency and instruction appeal of blended learning model.  

Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2, 87-105. http://dx.doi.org/10.1016/S1096-7516(00)00016-6   

Lancaster, M. (2022). Blended learning: impacts on the student experience (pp. 46–56). Edward Elgar Publishing Limited.  

Liu, Y., Chen, S., Feng, X., Bai, X., & Ma, Y. (2024). Supporting Students and Instructors in Blended Learning. In: Li, M., Han, X., Cheng, J. (eds) Handbook of Educational Reform Through Blended Learning. Springer, Singapore. https://doi.org/10.1007/978-981-99-6269-3_5    

Moule, P. (2006). E-learning for healthcare students: developing the communities of practice framework. Journal of Advanced Nursing, 54(3), 370–380.  

Moule, P. (2007). Challenging the five-stage model for e-learning: a new approach. ALT-J, 15(1), 37–50. https://doi.org/10.1080/09687760601129588  

O’Brien, M., & Freund, K. (2018). Lessons learned from introducing social media use in undergraduate economics research. International Journal of Education and Development using ICT, 14(1). https://www.learntech-lib.org/p/183552/   

Poon, J. (2013). Blended learning: An institutional approach for enhancing students’ learning experiences. Journal of online learning and teaching, 9(2), 271.  

Salmon, G. (2003). E-moderating (2nd ed.). Routledge Falmer.  

Sazdovska-Pigulovska, M. (2021). Impact of online education on student emotional well-being. Educational Role of Language Journal, 2021-2, 6-23. http://dx.doi.org/10.36534/erlj.2021.02.01 

Vaughan, N. (2007). Perspectives on blended learning in higher education. International Journal on E-Learning, 6(1), 81-94.  https://www.learntechlib.org/primary/p/6310/

 Willging, P. A., & Johnson, S. D. (2009). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks, 13(3), 115-127. http://dx.doi.org/10.24059/olj.v8i4.1814

Opportunities for Students’ Wellbeing: Enhancing Perceptions of Data Science through Data Storytelling in a Diverse Classroom Context

cdtlsd Poster , , , ,

Yiyun FAN1,*, Amanda Wan Mei SOON2, and Kah Loon NG1,*

1Faculty of Science, National University of Singapore (NUS)
2Office of Provost, NUS

*yiyunfan@nus.edu.sg; *kloon@nus.edu.sg

Fan, Y., Soon, A. W. M., & Ng, K. L. (2024). Opportunities for students’ wellbeing: Enhancing perceptions of data science through data storytelling in a diverse classroom context [Poster presentation]. In Higher Education Conference in Singapore (HECS) 2024, 3 December, National University of Singapore.https://blog.nus.edu.sg/hecs/hecs2024-yyfan-et-al/

SUB-THEME

Opportunities from Wellbeing

KEYWORDS

Student wellbeing, data storytelling (DS), learning perceptions, data science, diverse classroom

CATEGORY

Paper Presentation

EXTENDED ABSTRACT

Data science has emerged as a prominent discussion topic in education. Increasingly, students from underrepresented majors in non-STEM fields are showing interest in the data science industry, recognising its potential to enhance their research or employment opportunities. This trend is underscored by workplace phenomena, for instance, where recruiters in the UK may be more inclined to favour STEM students over non-STEM ones due to the latter often lacking STEM skills such as mathematics application and programming and being more difficult/expensive for employers to train (Grinis, 2017). This has highlighted the growing importance of such skills and the advantages they confer in the job market. However, as more entry-level courses in data science are introduced at university levels to address this trend, students, particularly non-STEM ones, have reported experiencing difficulty in learning courses that seem unrelated to their professional fields. This increased workload exacerbates their academic challenges and adds to their overall stress levels. For instance, feedback from a general introductory data science course revealed that 5.8% of comments were negative. Students expressed their stress from learning data analysis software. This rate increased to 10.4% the following semester and 12.1% the semester after (personal communication, June 20, 2024).

 

Data Storytelling (DS) utilises storytelling elements to compress information and convey key elements through narratives and data visualisations (Ryan, 2016), and holds the potential for enhancing learning experiences. It has been reported by recent scholars that DS elements, albeit with limited pedagogical constructs, have a promising future in educational settings (e.g., Chen et al., 2019; Echeverria et al., 2018; Martinez-Maldonado et al., 2020).

 

Many previous scholarly works have tackled the challenge of developing course curriculum that not only attract students from diverse backgrounds (e.g. gender and ethnicity group disparities) but also foster “communication, reasoning and collaboration that cross disciplinary boundaries” (Dierker et al., 2017, p. 55). However, few studies have investigated the impact of students’ academic major backgrounds and their related concerns, which are becoming increasingly relevant in today’s job market. Building upon this gap, this study examines the role of DS as supplementary material in the curriculum to introduce elementary data science skills to students through engaging narratives and data visualisations. By integrating DS into the course, this study aims to help students, particularly those with non-STEM backgrounds, better adapt to the current educational trend, thereby reducing their stress and improving their perceptions of learning data science.

 

The primary analysis method in this study involves qualitative analysis of students’ written and interview feedback after engaging with data stories based on the content of a general data science course at a prestigious university in Singapore. This study explores students’ perceptions of DS and their expectations of its role in future application in educational settings. Notably, feedback from non-STEM students, collected after their review of DS based on a random dataset, reveals their overall positive perspectives on the use of DS to support and improve the curriculum. Recurrent feedback items include students’ desire for more concise data stories integrated into data science skill introduction and their interest in engaging with more stories like these. This feedback highlights the potential of DS to assist students from various academic backgrounds, particularly non-STEM ones, in understanding and appreciating data science, thus reducing their stress in learning.

REFERENCES

Chen, Q., Li, Z., Pong, T.-C., & Qu, H. (2019). Designing Narrative Slideshows for Learning Analytics. In Proceedings of the IEEE Pacific Visualization Symposium, PacificVis’19 (pp. 237–246). https://doi.org/10.1109/PacificVis.2019.00036.

Dierker, L., Ward, N., Alexander, J., & Donate, E. (2017). Engaging underrepresented high school students in data driven storytelling: An examination of learning experiences and outcomes for a cohort of rising seniors enrolled in the gaining early awareness and readiness for undergraduate program (GEAR UP). Journal of Education and Training Studies, 5(4), 54–63. https://doi.org/10.11114/jets.v5i4.2187

Echeverria, V., Martinez-Maldonado, R., Shum, S. B., Chiluiza, K., Granda, R., & Conati, C. (2018). Exploratory versus explanatory visual learning analytics: Driving teachers’ attention through educational data storytelling. Journal of Learning Analytics, 5(3), 72– 97. doi: http://dx.doi.org/10.18608/jla.2018.53.6

Grinis, I. (2017). The STEM Requirements of “Non-STEM” Jobs: Evidence from UK Online Vacancy Postings and Implications for Skills & Knowledge Shortages. Systemic Risk Centre.

Martinez-Maldonado, R., Echeverria, V., Nieto, G. F., Shum, S. B. (2020). From data to insights: A layered storytelling approach for multimodal learning analytics [Paper presentation]. In CHI ’20 Conference on Human Factors in Computing Systems, April 25–30, 2020, Honolulu, HI, USA.

Ryan, L. (2016). The Visual Imperative: Creating a Visual Culture of Data Discovery. Elsevier Science.

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