The impact of post-event information on study-related memories: An exploration of the roles of judgemental anchoring, specific expectations about change, and motivational influences

Abstract

We explored how well common theories about the impact of post-event information on memories explain recollections that occur naturally in university students’ study routines. Instead of starting from a familiar research paradigm, such as those used in hindsight-bias research, the present study used a situation common to university students, and examined how well three candidate explanations—judgemental anchoring, implicit theories of change, and motivational influences—could explain the results we obtained in a long-term memory study that included three sessions, six months apart. We found that about two thirds of the memories of study-related issues were indeed biased, and that the impact of post-event information being used as an anchor is the most plausible explanation for the results. There were also some indications that memory biases might have been due, at least in part, to motivational factors.

Acknowledgments

We would like to thank Tilmann Betsch, Hartmut Blank, Anita Hewer, Anita Todd, and two anonymous reviewers for their helpful comments on an earlier version of the paper.

Notes

¹Sometimes, in so-called hypothetical designs, the first step is omitted, and effects of the new information are examined by comparing the hypothetical recollections (“What would have been your judgement back then?”) of participants who actually received the new information with ones who did not.

²There are, of course, also some exceptions to the typical procedure in hindsight bias studies that have used more personally relevant questions and longer intervals, such as, for instance, Renner (2003), Stahlberg, Eller, Romahn, and Frey (1993), or Mark and Mellor (1991).

³The material used in all parts of the study was originally in German.

⁴We counted a response as correct if it matched the original judgement or prediction exactly. One might object that this criterion is too strict, because it is difficult to remember an arbitrary number. However, an inspection of the judgements or predictions revealed that 96% of all judgements in session 1 were multiples of 10 or 5, and so were 94% of all judgements in session 2. Thus, numbers were relatively easy to remember.

⁵In Germany, places for psychology students are restricted and are mainly distributed by a federal agency. Because there are many more applicants than free spaces, many students who are not granted a space try to get into the psychology programme of any university by petitioning these universities, because once admitted to any programme, students can change universities. For the semester in question, about 90 students petitioned Chemnitz University of Technology to get admitted, to the psychology programme. A large number of the plaintiffs were, in fact, admitted but left the university again after completion of the first semester.

⁶We restricted ourselves to three linear patterns because the period concerned is relatively short, and opinions are therefore assumed to change (if they change) only in a way that can be roughly described as linear.

⁷In Germany, the best occasion to change universities is after the “Vordiplom”, which is roughly comparable to the bachelor's degree, and which is usually obtained after two years of study.

⁸A pattern was coded as stable if recollections and current judgements were identical, as an increase if current judgements were higher than the recollections, and as a decrease if current judgements were lower than the recollections.

⁹LOWESS lines (short for locally weighted scatterplot smoother; Cleveland, 1985) are a powerful technique to visualise all kinds of relationships between two variables. It is a stepwise smoothing technique that in each step (along the x axis) only takes into account a certain percentage of all data points and, in addition, weighs close data points more strongly than far-away ones. Thereby, the influence of any outliers on the line is minimised. If the relationship between the two variables is linear, LOWESS and regression lines are identical.