Stephanie Boragina

@sboragina.bsky.social

722 Followers 1200 Following

🇨🇦 PhD student and instructional designer of online courses Studying math education at the postsecondary level. Currently examining the growth of student mathematical understanding when taking asynchronous online math classes. #MathEd #OnlineEd

No lesson learnt To investigate whether skills are being lost in the field of computer science, researchers at the Al firm Anthropic in San Francisco, California, designed a randomized controlled trial in which 52 software engineers were asked to perform a basic coding task³. During the exercise, all 52 participants could search the web and access instructions on how to do the task. Half of the participants were prompted to use an Al assistant as well. Afterwards, all of the software engineers were asked to complete a quiz about what they had learnt from the task. The participants who had used an Al assistant did significantly worse on the quiz than those who hadn't: the average (continues on next image)
TEP- AIED is at the intersection of Transparency - System specification - Prompt design - Reproducibility Ethics - Data governance - Risk mitigation - Equity and access Pedagogy - Learning objectives - Al instructional role - Learner orientation
The pedagogical solution: From cognitive atrophy to augmentation The evidence for detrimental offloading is compelling, but it is not deterministic. The technology itself does not seal the outcome. As Kalyuga and Plass (2025) argue in their update to Cognitive Load Theory, the goal of the student matters, as does their motivation. Much of the research to date has yet to grapple with this added complexity. As Weidlich et al. (2025) argue in their methodological critique, much of the research on Al is an "effect in search of a cause," because it conflates the medium (the Al tool) with the instructional method (the pedagogy). They argue that pedagogy is the causal factor, and the research provides clear, evidence-informed pathways for a pedagogy that mitigates the risks posed by Al outsourcing. Not only is goal setting (a component of self-regulated learning) critical here, but other aspects of students' capability to manage their own learning and thinking also need to be supported through their learning experiences. That said, the pedagogical design of the tools used in instruction can influence whether students engage in positive or negative cognitive offloading. Al tools vary in their integration of educational evidence and construction of learning pathways and they increasingly form a mediating layer between curriculum and delivery in the classroom (Loble & Stephens 2024a). Path 1: Beneficial offloading and load reduction instruction Al can be used for beneficial offloading, managing extraneous load to free resources for intrinsic learning. This requires an explicit pedagogical framework. Martin et al. (2025) provide such a framework, "Load Reduction Instruction" (LRI), which adapts explicit instruction principles useful for managing learning with Al.
De-anthropomorphizing "AI": From wishful mnem... 4.2.2. The Products of cognition category Closely related to the Cognizer category but subtly distinct is the category of Products of cognition. These are expressions that refer to something that the system supposedly has, but could only have gained through cognitive activity, such as skills, capabilities, or a sense of aesthetics. The first two are anthropomorphizing descriptions of what would be better described as functionalities. That is, they describe a potentially real property of the system, but do so misleadingly by drawing on metaphors of learning in people. With sense of aesthetics the anthropomorphizing language is even more misleading, locating within the system something that actually belongs to the people involved: those curating the training data and those perceiving system output.
This correlation between neural connectivity and behavioral quoting failure in LLM group's participants offers evidence that: 1. Early Al reliance may result in shallow encoding. LLM group's poor recall and incorrect quoting is a possible indicator that their essays were not internally integrated, likely due to outsourced cognitive processing to the LLM. 2. Withholding LLM tools during early stages might support memory formation. Brain-only group's stronger behavioral recall, supported by more robust EEG connectivity, suggests hat initial unaided effort promoted durable memory traces, enabling more effective reactivation even when LLM tools were introduced later 3. Metacognitive engagement is higher in the Brain-to-LLM group. Brain-only group might have mentally compared their past unaided efforts with tool-generated suggestions (as supported by their comments during the interviews), engaging in self-reflection and elaborative rehearsal, a process linked to executive control and semantic integration, as seen in their EEG profile. The significant gap in quoting accuracy between reassigned LLM and Brain-only groups was not merely a behavioral artifact; it is mirrored in the structure and strength of their neural connectivity. The LLM-to-Brain group's early dependence on LLM tools appeared to have impaired long-term semantic retention and contextual memory, limiting their ability to reconstruct content without assistance. In contrast, Brain-to-LLM participants could leverage tools more strategically, resulting in stronger performance and more cohesive neural signatures.
Participants were randomly assigned across the three following groups, balanced with respect to age and gender: 1. LLM Group (Group 1): Participants in this group were restricted to using OpenAl's GPT-40 as their sole resource of information for the essay writing task. No other browsers or other apps were allowed; 2. Search Engine Group (Group 2): Participants in this group could use any website to help them with their essay writing task, but ChatGPT or any other LLM was explicitly prohibited; all participants used Google as a browser of choice. Google search and other search engines had "-ai" added on any queries, so no Al enhanced answers were used by the Search Engine group. 3. Brain-only Group (Group 3): Participants in this group were forbidden from using both LLM and any online websites for consultation.
Portion of quote visible on mobile (full quote isn't visible as it seems quotes are in a fixed-width box that is wider than the mobile screen; also, these quotes are automatically scrolling and there is no obvious way to stop the scrolling or reverse it). Front end of each line is cut off so you just see: ...enter is an intuitive, powerful tool ...ed to save you time and boost your ...fficiency, all while offering a user- ...y interface that makes creating ...tations a breeze." - Kim Ngan, Teacher
Solution: Rows: 8 + 3 + 11 + 10 = 32 13 + 4 + 16 + 15 = 48 12 + 1 + 9 + 14 = 36 5 + 2 + 7 + 6 = 20 Columns add to 38, 10, 43, and 44 Middle square consists of square numbers 4, 16, 1, 9