The ability to read and understand dense academic work is very important for any student. This sample article review from Ultius reviews and synthesizes arguments from a psychology study regarding goal conflicts and the relationship with complex problem solving.
Article Review: “How Induced Goal Conflicts Affect Complex Problem Solving”
The article from The Open Psychology Journal titled, “You Cannot Have Your Cake and Eat it Too: How Induced Goal Conflicts Affect Complex Problem Solving” consisted of two experiments and five separate hypotheses. For the purposes of this article review, the focus will be on Experiment One and Hypothesis One.
First experiment with psychology and motivation
Experiment one involved a computer simulation with predefined, weighted goals. Depending on which study group the participants were in, the goals were either independent, compatible, or interfered with each other. The purpose was to have the conflict demands on the participant inflict demotivation and symptoms of lower well-being. The alternative hypothesis is stated as,
In complex problem situations involving antagonistic goal relations, problem solvers report losses of current motivation. We expect measures of current motivation to decrease in problem-solving situations of antagonistic structure since antagonism implies at least partial non- attainment of goals. Given that two goal states cannot be achieved at the same time, subjects should be prompted to settle for moderate success concerning both goals or they might accept failure for one goal combined with success for the complementary goal.
Whereas in real life further strategies might be conceived (e.g., striving for one goal first and for the other goal next, trying to find common aspects to link both goals on a conceptual level), according to our understanding of goal antagonism, goal redefinitions are limited. Disappointment is therefore pre-assigned in either case, independent of individual goal management. The feasible assumption that goal failure induces low motivation finds empirical support for both long-term strivings and relatively straightforward achievement tasks in experimental settings. Mediated by pre-installed (partial) failure, participants should suffer from losses in current motivation (Blech & Funke, 2009).
Null hypothesis for problem solving
On the other hand, the null hypothesis would simply be: in complex problem situations involving antagonistic goal relations, problem solvers do not report losses of current motivation. The researchers do not satisfactorily reject the null hypothesis. Instead, Blech and Funke make a soft statement,
multitasking-like scenarios usually imply goal conflicts because time management or limitations in cognitive capacity force a person to abandon goals or subgoals. However, they do not guarantee conflicts, and the degree of conflict may vary with an individual’s skill, ability, and experience. To lessen the impact of interpersonal differences and to ensure that conflicts will definitely occur we decided in favor of a direct conflict manipulation implemented in a computer program (2009).
Before delving into the research variables, it would be beneficial to explain several key definitions. The first term, goal independence, is simply pursuing goal A will have no impact, positive or negative, on goal B and vice versa. The second term, goal compatibility or goal synergy, means
“achieving goal A increases the probability of achieving goal B at the same time” (Blech & Funke, 2009).
The third crucial term is, goal interference, and contains two parts.
- Part one says goal A and goal B cannot be achieved at the same time without extra effort.
- Part two states that goal A and goal B cannot be achieved simultaneously, no matter what.
If the first definition is not applicable the second one applies.
Breakdown of experiment one
The experiment places the participants in the shoes of an entrepreneurial ship owner. The participants must manipulate four goals simultaneously to achieve the most desirable outcome. Goals include:
- (a) Contentment of passengers and goal
- (b) Productivity of employees are dependent upon each other and together function independently of goal
- (c) Quality of management and goal
- (d) Public reputation of ship owner
Goals C and D are dependent upon each other. Each of the options within each goal category has been given a weight. In terms of motivating employees to increase productivity, the weighted amount in turn determines the ‘effectiveness’ of that choice within the goal category. For example, the variables found in goal B, productivity of employees are as follows:
- A highly effective measure such as ‘increase payment of wages’ would yield a weight of 4 points
- A moderately effective measure such as ‘renovate staff canteen’ would yield a weight of 2 points
- A non-effective measure such as ‘apply recruitment tests’ would yield a weight of 0 points (Blech & Funke, 2009).
Psychology and motivation: problem solving skills
The variables from our list that can be manipulated by the participant are called the input or exogenous variables. The two-goal version of our scenario (Experiment 1) involves 18 such variables. Endogenous variables in Experiment 1 are the two goal variables of:
- Contentment of passengers (CP)
- Productivity of employees (PE)
The four goal variables are:
- Contentment of passengers (CP)
- Productivity of employees (PE) as measured through motivational endeavors
- Quality of management
- Public reputation of ship owner (Blech & Funke, 2009).
Measurement of variables
The level of measurement for Blech and Funke’s variables follows:
For all exogenous variables chosen during an intervention step, the corresponding weight scores will be summed up. In order to prevent that subjects simply pick all exogenous variables, cost scores will be subtracted. Costs are implemented so that selecting the full range of interventions will neither yield an increase nor a decrease in the goal scores. Instead, to raise goal scores, participants are challenged to experiment and search for effective single or combined measures from the intervention list (2009).
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Participant measurements for psychology and motivation
The study’s participant measurements were obtained by the following methods.
- The upper part displays achievement status for both goal demands by score numbers
- Horizontal bars represent the score graphically
- Arrows indicate either an upward, downward, or a constant development of goal scores
- From the lists below, users point and click boxes to select or deselect relevant measurements by visible check marks.
- Once they have finished, they submit their inputs by operating the ‘finished’ button, then switching to a new simulation month, i.e., a new intervention step.
- Check marks from the previous month are then removed.
Participants run through a sequence of ten such interdependent steps. From the instruction, participants were encouraged to start their exploration on the base of pre-existing knowledge and plausibility (Blech & Funke, 2009).
Stress results of participants
Calculating stress results from the participant’s activity was gathered by the following means:
Experienced stress symptoms were retrieved by 12 items of a self-report 7-point Likert scale that was constructed from dimensions of perceived stress symptoms according to Kohli , e.g.
Another 10-item self-report questionnaire (5-point Likert scale) asked about styles of subjects’ intervening manipulations (Blech & Funke, 2009).
Blech, C., & Funke, J. (2009). You cannot have your cake and eat it too: how induced goal conflicts affect complex problem solving. The Open Psychology Journal. Retrieved from http://cogprints.org/6867/1/Blech%26Funke_2010_Polytely.pdf