DLEAEP

Effects of Different Learning Experiences on Automatic Evaluative Processes

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 Obiettivo del progetto (Objective)

'In evaluative learning, associative learning refers to the effect of repeated exposure to an object and an evaluation that appear together (e.g., “Snakes-Unpleasantness”), whereas propositional learning refers to learning the actual relationship between the object and the evaluation (e.g., “Snakes cause unpleasantness”). A common core assumption in contemporary attitude research is that associative learning affects mainly automatic evaluations (unintentional and sometimes unconscious), whereas propositional learning affects mainly controlled evaluations (deliberated and conscious). However, contemporary attitude theory acknowledges some relationships across the implicit/explicit boundary. The proposed research will extend the investigation of these assumed relationships by examining another possible interrelation across the implicit/explicit boundary: the effect of non-associative information on automatic evaluations. The research will examine how learning specific object-evaluation relationships (e.g., “X causes unpleasantness” vs. “X prevents unpleasantness”) affect implicit measures and automatic evaluation. The research includes unprecedented large-scale (overall N > 30,000) comparative studies that will examine current assumptions about implicit/explicit distinctions in formation and measurement, in addition to the effect of propositional learning on automatic evaluation. It will use a large number of associative and propositional attitude induction methods, four difference implicit measures, and attitude-relevant automatic behaviors. These large-scale tests are possible because of the researcher’s involvement in an American research website that collects data from thousands of participants every week. At the same time, the research will test these questions in smaller-scale lab-studies with a subset of the same learning procedures and attitude measurements, but with attitude-relevant social interactions created in an immersive virtual reality environment.'

Introduzione (Teaser)

EU funding supported a study extending knowledge on evaluative learning processes. The research examined evaluations (i.e. automatic) and conscious (i.e. controlled) assessments.

Descrizione progetto (Article)

With a general focus on psychological processes contributing to the formation of attitudes, the project 'Effects of different learning experiences on automatic evaluative processes' (DLEAEP) began with contemporary attitude theory. This approach acknowledges relationships beyond the implicit/explicit boundary.

Specifically, research delved into assumptions regarding learning experiences on automatic versus controlled evaluation. The former involves fast, unintentional and sometimes unconscious processes. The latter involves intentional, effort-directed cognitive processes producing judgment related decisions as to whether a person likes or dislikes an object.

Using a variety of experimental procedures, DLEAEP produced evidence supporting, as well as slightly modifying, this basic assumption. The results explain the boundary conditions and add details regarding the processes potentially contributing to the assumed discrepancy (differences).

One research strand focused on relational information, which indicates that objects are associated with each other and also explains why and how. One example of such information is: 'The bacteria ended the inflammation.' This indicates there is an association between the bacteria and the inflammation, and explains the nature of their association. This form of information can produce mental links in memory.

Following up, the study offered evidence that relational information leads to associations that likely influence both automatic evaluation and controlled evaluation at a later date. DLEAEP found that the first is more sensitive to associative information (bacteria and inflammation are associated), and the second to relational information (bacteria ends inflammation).

One significant finding was an automatic preference for objects ending pleasant events over objects ending unpleasant events. Research also highlighted under what conditions such counter-intuitive automatic preference occurs and how it can be increased or eliminated.

Other project research involved the study of how different learning experiences impact different measures of automatic evaluation. The team developed a theoretical framework to generate hypotheses on the effects of stimuli co-occurrence on later evaluations.

DLEAEP's large-scale tests and smaller-scale laboratory studies have made an important scientific contribution to the body of knowledge on psychological evaluative processes.