Repetition learning is neither a continuous nor an implicit process

Abstract

Learning advances through repetition. A classic paradigm for studying this process is the Hebb Repetition Effect: immediate serial recall performance improves for lists presented repeatedly as compared to non-repeated lists. Learning in the Hebb paradigm has been described as a slow but continuous accumulation of long-term memory traces over repetitions (e.g., Page & Norris, 2009). Furthermore, it has been argued that Hebb repetition learning requires no awareness of the repetition, thereby being an instance of implicit learning (e.g., Guérard et al., 2011; McKelvie, 1987). While these assumptions match the data from a group level perspective, another picture emerges when analyzing data on the individual level. We used a new Bayesian hierarchical mixture model to describe individual learning curves. In two preregistered experiments, using a visual and a verbal Hebb repetition task, we demonstrate that (1) individual learning curves show an abrupt increase with a variable time for the onset of learning across individuals, and that (2) learning onset depended on participants becoming aware of the repetition. These results imply that repetition learning is not implicit, and that the appearance of a slow and gradual accumulation of knowledge is an artifact of averaging over individual learning curves.

Testing Expectations and Retrieval Practice Modulate Repetition Learning of Visuo-Spatial Arrays

“…Although this assumption was not directly tested in the present study nor in the study from Souza and Oberauer (2022), we provide strong evidence for this claim in yet another project, by showing that repetition learning effects only occurred after participants became aware of the repetition and hence, were able to explicitly recognize the repeated information (Musfeld et al, 2022).…”

“…Again, this would cause a less informative representation of the trial in episodic memory and decreased chances of successful recognition. Therefore, the testing expectations mainly influence the chance of recognizing previous encounters of the same information, which we propose is necessary to initiate the learning process (Musfeld et al, 2022;. The actual retrieval demands during the working memory test, however, influence the strengthening process of the memory trace itself.…”

Promoting visual long-term memories: When do we learn from repetitions of visuospatial arrays?

“…We continue to be intrigued by the conditions that favor visuospatial learning. For example, we are currently investigating whether single-item tests prevent learning, or just prevent people from using it (Musfeld et al, 2021). We also started investigating the role of awareness of the repetition for Hebb learning (Musfeld et al, 2022).…”

“…For example, we are currently investigating whether single-item tests prevent learning, or just prevent people from using it (Musfeld et al, 2021). We also started investigating the role of awareness of the repetition for Hebb learning (Musfeld et al, 2022). The present work contributes one piece to the puzzle that permits to understand how information flows from working memory to long-term memory and vice-versa.…”

If God Handed Us the Ground-Truth Theory of Memory, How Would We Recognize It?

“…Most of the time we pay lip service to individual differences in our modeling work -we all agree they are important, and much valuable empirical research has gone into understanding how and when people differ in their memory ability. Yet, despite regularly appearing articles that bring attention to the pitfalls of ignoring such differences in modeling (Estes, 1956(Estes, , 2002Gallistel et al, 2004;Musfeld et al, 2022), most of our efforts have gone into modeling aggregated effects.…”