Whereas the communicative logic of the old media was linear (knowledge creator to passive knowledge consumer), new media is dialogical and recursive, to the point even where it is hard to distinguish creator and consumer (Kalantzis & Cope, 2015). Feedback is pervasive. Web reputation and moderation systems add social filters to the feedback (Farmer and Glass, 2010).

New media enables a renewed focus on formative assessment – assessment that is on-the-fly, and that makes in a detailed and con-structive way a direct contribution to student learning (Black and William, 1998; William, 2011). In the era of social knowledge technologies, no learning environment should be without always-available feedback mechanisms – machine feedbaE4RCck and machine-mediated social feedback (Kalantzis & Cope, 2015)

Behrens and DiCerbo (2013) argue that: technology allows us to expand our thinking about evidence. Digital systems allow us to capture stream or trace data from students’ interactions. This data has the potential to provide insight into the processes that students use to arrive at the final product (traditionally the only graded portion). As the activities, and contexts of our activities, become increasingly digital, the need for separate assessment activities should be brought increasingly into question. (2013, p. 9).

Chung traces the consequences for education in these terms: Technology-based tasks can be instrumented to record fine-grained observations about what students do in the task as well as capture the con-text surrounding the behavior. Advances in how such data are conceptualized, in storing and accessing large amounts of data (‘big data’), and in the availability of analysis techniques that provide the capability to discover patterns from big data are spurring innovative uses for assessment and instructional purposes. One significant implication of the higher resolving power of technology-based measurement is its use to improve learning via individualized instruction. (Chung, 2013, p. 3). As well as being able to measure individual work, we can measure social interactions and peers’ contributions to others in the form of the feedback they have provided. In other words, we can assess learning interactions as well as learning artefacts. We could even take a more audacious step, in the direction of a ‘no failure’ educational paradigm, where you can keep taking on feedback until you are as good as good is supposed to be. This is by way of contrast with the distribution of students across a bell curve, where the few can succeed only because most are destined to be mediocre or fail. A culture of mutually supportive con-structive feedback not only models the ideals of a knowledge economy where teamwork and networked collaborations are more valuable than ever; assistance helps the stronger as well as the weaker. It sets community standards, where the weaker see models in the works they review that are stronger and the completed works of peers published to a web portfolio. (Kalantzis & Cope, 2015)

Fig 1: Taxonomy of Courses in Architectural Education

Source: Eman S. Abo Wardah, 2020

Within the learning ecology of Architecture Design Studio, students are subjected to multi-concepts of recursive feedback which include: Formative assessment, Continuous assessment, Criterion-referenced (versus norm-referenced) assessment and Peer review.

The design project, which is the main content of the course syllabus in the design studio, is performing through different phases, and each phase in following one of more concept of recursive feedback. That starts from first phase of (project research), going through different design phases and ending with the final evaluation jury.

References:

Chung, G. (2013) ‘Toward the Relational Management of Educational Measurement Data’, The Gordon Commission, Princeton NJ.

DiCerbo, K. and Behrens, J. (2014) Impacts of the Digital Ocean on Education, London: Pearson.

Eman S. Abo Wardah, 2020, Bridging the gap between research and schematic design phases in teaching architectural graduation projects, Frontiers of Architectural Research, Volume 9, Issue 1, 2020, Pages 82-105, ISSN 2095-2635, https://doi.org/10.1016/j.foar.2019.04.005. Retrieved in August 13th from: (http://www.sciencedirect.com/science/article/pii/S2095263519300299)

Kalantzis, Mary and Cope, Bill, 2015, Learning and New Media, book chapter 35, The SAGE Handbook of Learning. P 373-379.