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E-Pedagogy in support of AfL and AFAL

E-Pedagogy in support of AfL and AFAL: What does it do for all learners?
by Rachel Goh

The theme for this issue is E-Pedagogy (E-Ped) in support of AfL and AFAL. While various definitions of E-Ped have been offered (e.g., Baldins, 2016), I prefer the conceptualisation of E-Ped as “approaches to teaching that utilize the affordances of digital information and communication technologies” (Way, 2009). This view contrasts a narrower conception of E-Ped as an assemblage of teaching strategies for E-learning.

There is an ongoing debate about whether E-Ped is a branch of pedagogy (Baldins, 2016), understood as educational practice informed by particular learning theory (e.g., behaviorism, cognitivism, social constructivism, etc.), or is “a radically different vision of pedagogy based on soft skills and digital literacies” (Livingstone, 2012, p. 9). Beyond such a binary quandary, a more generative way in theorizing, is perhaps to consider the argument of E-Ped as reflexive pedagogy that draws on different learning theories, decisions about which is most apt flow from the judgement as to the intended learning outcomes (Kalantzis & Cope, 2020; James, 2006).

In this regard, a principled approach to E-Ped would support the ambitious views of employing E-Ped intended “to accelerate and deepen learning by making it more active and personalized” (MOE, 2020a) and “for active learning that creates a participatory, connected and reflective classroom to nurture the future-ready learner” (MOE, 2020b). If E-Ped is to be employed to deepen students’ learning, it would not be difficult to make the connection to how it hinges on supporting AfL with the ultimate goal of getting students “to take ownership by playing an active role in the process of learning in school and beyond” (Leong, Ismail, Tay, Tan, & Lin, 2019).

So, how can E-Ped support a learner-centred AfL process for all learners?

Watch this video for an overview of the discussion on E-Ped in support of AfL and AFAL.

 

The COVID-19 pandemic has thrusted us into home-based learning at a time when face-to-face interactions are constrained. While the best of technological tools cannot fully replicate learning conditions afforded by in-person human interactions, digital affordances, when harnessed appropriately, can enhance learning and enable different meaningful learning experiences, in and beyond the physical classroom. Drawing from published literature and school practices, examples will be presented on how digital technologies have been harnessed to elicit evidence on where students are in their learning, engage them in quality feedback, and elevate their role in assessment.

We begin by describing three technology-enabled strategies that may be employed separately or in combination at the substitution or augmentation levels to enhance AfL (Puentedura, 2013). Then, how technology can be harnessed to modify task design to enable deep learning will be discussed. Finally, an example will be presented to illustrate the affordances of technology in redefining student learning, specifically in enabling the development of student voice.

The three technology-enabled strategies that are of interest are the use of: (1) online knowledge surveys, (2) online student-generated questions and peer responses, and (3) electronic reflective journals.

  • Online knowledge surveys are employed to elicit information on student understanding, and the evidence of which is used formatively for course design/redesign. A knowledge survey consists of a set of questions that cover the content of the course, which students answer by responding to a rating scale of their confidence to respond with competence to each question (Bahati, Fors, Hansen, Nouri, & Mukama, 2019). Knowledge survey practices can serve formative assessment purposes by giving students opportunities to self-assess their understanding and learning gaps at key junctures as the course progresses. While a knowledge survey, in and of itself, may be a poor indicator of learning, gains in student self-efficacy were reported when comparing pre- and post-instruction self-assessment surveys (Bowers, Brandon, & Hill, 2005; Clauss & Geedey, 2010). The implication for tech-enabled self-assessment to support all learners is the need to raise student awareness of the different resources they can tap to close the identified learning gaps, for example, revising self-study materials, engaging in peer/teacher dialogue to clarify understanding, etc.
  • Getting students to generate learning material-related questions and respond to one another’s questions are ways of activating students as learning resources for one another (Wiliam & Leahy, 2016). The feature article on the practice in Juying Secondary School provides an illustrative case of peer assessment enabled through the affordances of Flipgrid in the context of blended learning for the teaching of oracy in Ms Lau Jia Yun’s classroom. Click here to view the article and video.
  • Journals, enabled by technology such as Google documents, can offer a digital learning space for student reflection beyond the limits of physical records. When well-designed, journal prompts and tasks help students reflect on critical learning incidents and/or learning interactions over a given period of time (Thorpe, 2004). Electronic reflective journals, when used in support of AfL, can be used to prompt students to pose questions to elicit teacher feedback on their written work. This can help teachers offer more focused feedback and gain insights on student thinking. The affordances enabled through in-text comments allow students to respond to the teacher’s questions/comments, create a digital space to extend dialogic feedback, and provide a reference for future work.

In the study by Bahati et al. (2019) where 109 pre-service teachers were surveyed, the results showed that the online knowledge survey was an e-assessment strategy that the participants were mostly satisfied with in terms of both quality of engagement and quality of feedback. This was followed by electronic reflective journals and online student-generated questions. The study found no relationship between the students’ scores and learner satisfaction with aspects of blended learning, unlike another study (Chitkushev, Vodenska, & Zlateva, 2014). While the link between learner performance and learner satisfaction with the elements of blended learning is not definitive, the affordances of E-Ped to promote greater student agency and ownership of their learning lends weight to the curriculum imperative for using E-Ped to support all learners.

Beyond the inclusion of one or more technology-enabled strategies at the substitution or augmentation levels (Puentedura, 2013), technology can be harnessed to modify task design in support of AfL. In a study involving 410 first-year undergraduates in a psychology course, an online cognitive assessment tool (OCAT) was designed to employ different cognitive learning strategies to enable students to experience deep approach learning (DAL) as opposed to adopting a surface-approach to learning (SAL), characterized by rote memorization. The OCAT which takes a multiple-choice format begins with a free recall response where students can type as much information as they want in a dialogue box to enable active retrieval and help them experience “prime associations” (Shaw, MacIsaac, & Singleton-Jackson, 2019, p. 128). The OCAT offers retrieval cues for incorrect responses and second opportunities to answer questions for fewer marks, and ends with explanations for both correct/incorrect responses as immediate feedback. The study found that students regardless of whether they were learning-oriented (LO) or grade oriented (GO) had the highest level of engagement with the second opportunity feature, but only students who were high LO were taking advantage of the paired retrieval cues, such as taking time to read a text or review a video, to gain a deeper understanding of the material. This study illustrates the affordances of technology in enabling “repetitive attempts, retrieval cues and immediate feedback” (Shaw et al., 2009, p. 139) in transforming online tasks to support AfL. The implication for E-Ped in supporting all students, regardless of their academic-orientations, is to raise student awareness of the educative potential of the built-in cognitive learning features of online assessments to help them make the transition into deep approach learning.

Try this simple OCAT designed using Google Forms. Experience its affordances in supporting AfL through a combination of knowledge survey, retrieval cues, second tries, and immediate feedback.

 

In the final example, I want to present a case of how E-Ped transforms/redefines students’ learning experience to enable the development of student voice. The use of audio/video technology to complement written feedback is not new. What is gaining traction is the use of screen-casting technology to record verbal feedback with live annotations on student work which enables teachers to engage students in feedback beyond the limits of in-person interaction.

Keen to use screen-casting for tech-enabled feedback? Visit this link for curated how-to tutorials on using Zoom and Google Meet for screen-casting.
https://sites.google.com/view/assessment-literacy-for-all/home/AfL/Engaging

 

Minimally, the screen-cast video recording compels students to watch/listen to the feedback. The use of technology-enabled feedback in itself does not guarantee that students will take up the feedback. Opportunities to act on feedback need to be orchestrated by designing follow-up actions expected of students, be it in revising their writing or working on a parallel task.

Beyond harnessing digital technology to capture feedback, the study by Van der Kleij, Adie, and Cumming (2017) explored the use of video technology in enabling student voice in assessment feedback. Students were involved in video-stimulated recall of feedback conversations they had with their teacher and through viewing videos of their prior feedback interactions with teachers, they were able to self-reflect on their involvement in the feedback process and what they could/should have clarified, raised or discussed in the conversation. The study demonstrated the affordances of technology in elevating the role of students in assessments by encouraging them to make their voices heard, and allowing them to participate in feedback as a dialogic practice as opposed to a teacher monologue.

 

Beyond the “How to”, there are issues that are more intractable. Equity concerns argue that whether all students have access to such technology-enabled learning is fundamental (Klenowski, 2015). In the case of HBL in Singapore and elsewhere, “access is a far more complex issue than mere provision of facilities” (Furlong et al., 2000, p. 94). The availability of a computer, reported as a machine-to-student ratio, does not necessarily mean genuine access for all learners. The fact that there is provision for school use does not always mitigate the low access at home (Facer & Furlong, 2001), which is a current issue of concern in uplifting all students.

In this respect, the second feature article on school practice offers insights from parent surveys on their perspectives of the challenges and affordances of HBL. From their lived experience during the circuit-breaker, we can draw important implications on orchestrating necessary conditions to better support learning in the home front when in-person interactions in schools are constrained. Click here to read the article.

Beyond the practical considerations of HBL, we need to begin dialogue on making E-Ped supported AfL accountable for all learners in our specific contexts. How should we go about “ensuring that intended learning outcomes are achieved by ‸ALL students” (MOE, 2019)? What would E-Ped in support of AfL entail for the least, the last and the lost amongst our learners?

 

Suggested citation:

Goh, R. (2020). E-Pedagogy in support of AfL and AFAL: What does it do for all learners?. Assessment for All Learners (AfAL) Bulletin, October 2020.

 

References:
Bahati, B., Fors, U., Hansen, P., Nouri, J., & Mukama, E. (2019). Measuring learner satisfaction with formative e-assessment strategies. International Journal of Emerging Technologies in Learning, 14(7), 61–79. DOI 10.3991/ijet.v14i07.9120

Baldiņš, A. (2016). Insights into e-pedagogy concept development. Procedia-Social and Behavioral Sciences, 231, 251-255.

Bowers, N., Brandon, M., and Hill, C. D. (2005). The use of a knowledge survey as an indicator of student learning in an introductory biology course. Cell Biology Education, 4, 311-322.

Chitkushev, L., Vodenska, I., & Zlateva, T. (2014). Digital learning impact factors: Student satisfaction and performance in online courses. International Journal of Information and Education Technology, 4(4), 356.

Clauss, J. & Geedey, K. (2010). Knowledge surveys: Students ability to self-assess. Journal of the Scholarship of Teaching and Learning, 10, 14-24.

Facer, K. & Furlong, R. (2001), Beyond the myth of the ‘cyberkid’: Young people at the margins of the information revolution. Journal of Youth Studies, 4(4), 451-69.

Furlong, J., Furlong, K., Facer, K., & Sutherland. S. (2000). The national grid for learning: a curriculum without walls? Cambridge Journal of Education. 30(1), 91-110.

James, Mary. (2006). Assessment, Teaching and Theories of Learning. 47-60. 10.13140/2.1.5090.8960.

Kalantzis, M., & Cope, B. (2020). Introduction: The Digital Learner–Towards a Reflexive Pedagogy. In Handbook of Research on Digital Learning (pp. xviii-xxxi). IGI Global.

Klenowski, V. (2015). Fair assessment as social practice. Assessment Matters, 8, 76-93.

Leong, W. S., Ismail, H., Tay, H. Y., Tan, K., & Lin, R. (2019). Adopting learner-centred AfL process. [Brochure]. Singapore: Author.

Livingstone, S. (2012). Critical reflections on the benefits of ICT in education. Oxford review of education, 38(1), 9-24.

Ministry of Education Singapore. (2020a, August 19). Infosheet on SkillsFuture for Educators (SFED). https://www.moe.gov.sg/docs/default-source/document/media/press/2020/infosheet-on-SFEd.pdf

Ministry of Education Singapore. (2020b, September 15). Singapore Learning Designers Circle e-Bulletin Term 3/2020. https://drive.google.com/file/d/1HcgA4jvWTf2ZxVwXhtlensM4n4RCdwyc/view

Ministry of Education Singapore. (2019, June 20). Assessment concepts in assessment portal. Abstract retrieved from MOE Singapore intranet website OPAL.

Puentedura, R. R. (2013, May 29). SAMR: Moving from enhancement to transformation [Web log post]. Retrieved from http://www.hippasus.com/rrpweblog/archives/000095.html

Shaw, L., MacIsaac, J., & Singleton-Jackson, J. (2019). The efficacy of an online cognitive assessment tool for enhancing and improving student academic outcomes. Online Learning, 23(2), 124–144.

Thorpe, K. (2004). Reflective learning journals: From concept to practice. Reflective practice, 5(3), 327-343.

Van der Kleij, F., Adie, L., & Cumming, J. (2017). Using video technology to enable student voice in assessment feedback: Video, student voice and assessment feedback. British Journal of Educational Technology, 48(5), 1092–1105. https://doi.org/10.1111/bjet.12536

Way, J. (2009). Emerging E-Pedagogy in Australian Primary Schools. In Leo Tan Wee Hin & R. Subramaniam (Ed.), Handbook of Research on New Media Literacy at the K-12 Level: Issues and Challenges (pp. 588–606), London: IGI Global.

Wiliam, D., & Leahy, S. (2016). Embedding formative assessment. Hawker Brownlow Education.