Distractor Task Manipulation in Offline Associative Learning

Offline processing is regarded as the continued thought of information that occurs without explicit attention and outside of one’s conscious awareness, and it has been shown to be particularly advantageous in comparison to conscious thought and immediate testing in the realm of decision making. There is evidence for an underlying learning mechanism supported by offline processing, and recent work demonstrates advantages of offline processing in associative learning tasks. This study aims to address whether offline processing can be utilized as a practical technique in a real world learning task, and to investigate what specific types of distractor tasks best facilitate offline processing and learning. Participants encoded new real world information and were later tested on the material in either an immediate, same domain distractor, or different domain distractor condition in an online survey. Initial results indicate no advantage or disadvantage for either type of offline processing in comparison to immediate subsequent testing of newly encoded information. It is possible that this study presents evidence contrary to offline processing being a beneficial tool in real world learning, however, as such a newly investigated topic, this study more likely provides useful information as to what may or may not work in order to utilize offline processing in real world learning contexts. OFFLINE ASSOCIATIVE LEARNING 3 Offline Associative Learning Usually when attempting to learn, we try to actively engage ourselves as thoroughly as possible and use conscious, deliberate strategies to remember new information. Common theories on learning involve focus on conscious engagement from the learner, while offlineprocessing techniques have been a less pursued avenue in the learning domain. Offline processing is the continued thought of information that occurs without explicit attention and outside of one’s conscious awareness (Dijksterhuis & Nordgren, 2006). From what is currently known, there exists reasonable evidence to believe that offline processing techniques could be beneficially utilized in learning to boost information integration and consolidation, and in turn performance. This study aims to investigate whether offline processing can have an effect on real world associative learning performance, and whether the domain of distractor task utilized to produce offline processing has an impact on this effect. Research on offline processing, also known as unconscious thought, has detailed its characteristics as a mode of thinking. Offline processing and conscious thought are regarded as two different styles or modes of thinking, each having unique traits that can make one mode more advantageous than another depending on the circumstances. Of interest, offline processing is considered to have a large capacity in contrast to conscious thought, which is known to have a limited capacity (Strick, Dijksterhuis, Bos, Sjoerdsma, Baaren, & Nordgren, 2011). Offline processing has strengths in making rough estimates and holistic choices, while conscious thought is much better at following strict rules with precision. Offline processing thrives in environments where there is there is a large amount of information to integrate with no singular, correct outcome (Dijksterhaus, 2004). OFFLINE ASSOCIATIVE LEARNING 4 Offline processing has been well studied in the domain of complex decision making, which lends itself as an area favorable to this mode of thinking and it characteristic strengths. It has been demonstrated that when given a complex decision making task with numerous variables, participants who have a period of induced unconscious thought by completing a distractor task make better decisions than participants who make immediate decisions or are allowed to think about the choice consciously (Dijksterhaus, 2006). In these complex decision making studies, in order for participants to make final decisions, they must encode, consolidate, and integrate information that has been presented to them. The suggestion can be made that in these complex decision making tasks, there is an aspect of learning new information underlying the procedure and processes that benefit from offline processing. Recent research has investigated offline processing techniques in complex decision making tasks that has demonstrated neural evidence for reactivation of brain areas used in encoding during induced offline processing (Creswell, Bursley, & Satpute, A. 2013). It appears as though brain areas active during encoding of new information maintain activity during periods of induced offline processing through a distractor task, which leads to enhanced subsequent behavioral performance in making good decisions. This suggests that neural reactivation during offline processing allows for continued encoding of new information, which allows for enhanced behavioral performance, and that offline processing may involve a general mechanism for learning. Building on these findings, a recent study was conducted that tested offline processing within a declarative associative learning task using fictitious animal stimuli. Here, results show that a brief two minute period of induced offline processing through a distractor task boosts associative learning performance in the absence of conscious rehearsal. This novel associative OFFLINE ASSOCIATIVE LEARNING 5 learning paradigm suggests that periods of offline processing improve memory representations of learned associations due to encoded memory representations being reactivated during this time, as also demonstrated in the decision making tasks (Bursley, Nester, Tarr, & Creswell 2015). Furthermore, evidence has been shown that offline processes engaged in during sleep supports newly encoded associative memory links (Robertson, 2009). In rats, neural replay of maze running during sleep has been shown to improve later maze running performance, further suggesting evidence for enhancement through continued encoding of offline processes (Peyrache, Khamassi, Benchenane, Wiener, & Battaglia, 2009; Stickgold, 1998). While recent research has laid groundwork to suggest that offline processing techniques are beneficial in learning, this is counter to the majority of current learning theories and practices. Common learning theories assume that students should be using conscious rehearsal techniques to optimize learning of newly encoded information. For instance, the well-known self-regulated learning theory emphasizes control and autonomy of the learner to actively monitor and direct information acquisition (Paris & Paris, 2001). This theory includes using proactive practices such as problem-based learning, learning by assessment, rehearsal, and other activities with engaged, active involvement from the learner. Modern learning theories could be overlooking the potential advantages of utilizing offline processing techniques in the encoding and consolidation of new information as demonstrated by previous research. From investigations conducted so far, there is reasonable evidence to believe that offline processing will be beneficial to the encoding and consolidation of new information in a real world learning task, although previous work used a limited range of fictitious associative learning stimuli (Bursley et al., 2015). The goal of this study was to address the unknowns of implementing offline processing techniques in a real world associative learning context, and to OFFLINE ASSOCIATIVE LEARNING 6 investigate specifications around what type of task best induces facilitative offline processing. To address these questions in this study, participants encoded new information of real animal species that they were later assessed on. In order to investigate possible benefits of offline processing in learning, participants either completed the assessment immediately after encoding, or completed one of two distractor tasks. The two distractor tasks differed as to whether they were in the same domain as the previous encoding task or a different one. This domain manipulation allowed for investigation as to the specifications of a distractor task that will best induce the facilitative benefits of offline processing, either a task in the same domain as the previous encoding task or a task in a different domain from the previous encoding task. It is predicted that a different domain distractor task will allow for the facilitation of encoding by offline processing since it will be pulling from different resources in the brain than ones previously used during encoding, effectively allowing offline processing to continue. Accordingly, a same domain distractor task is predicted to not reap the facilitative benefits of offline processing due to interference. In this case, neural reactivation of regions responsible for offline processing will be disrupted by related distractor stimuli, eliminating offline processing benefits on learning. Specifically, it was predicted that offline processing is expected to enhance real world associative learning ability through facilitating encoding and consolidation as compared to immediate testing, but only when the distractor task that induces offline processing is in a different domain than previously encoded information. OFFLINE ASSOCIATIVE LEARNING 7 Methods Participants and Design: A total of 303 eligible participants were recruited through Amazon’s Mechanical Turk (MTurk) Artificial Artificial Intelligence marketplace for work and completed the study online on a personal computer. Participants received a set amount of $0.50 for completing the Human Intelligence Task (HIT). All participants were electronically randomized to one of three conditions and completed the study individually. Participants could only complete the study if they were over the age of 18, living within the U.S., and provided informed consent. Further exclusions were made to 11 participants for not fully completing the study or for taking an