Why Learning And Development Efforts Misuse Gamification (One-Size-Does-Not-Fit-All)

Recommended Audience: Chief Learning Officers, Chief Human Resources Officers, Learning and Development directors and managers, Corporate Trainers, Enterprise Librarians and Content Managers, Instructional Designers, Corporate Communications, Product Managers with a Content or Learning focus.

Key Takeaway: L&D-based gamification is ignoring major swathes of personality and human motivation, which prevents most current business approaches of gamification from being effective.

A psychological theory that I and other proposed (Maddox, Markman, & Baldwin, 2007; Maddox & Markman, 2010), and for which I obtained a $1 million grant from the National Institutes of Health to test, argues that cognitive effort is determined by the interaction of global and local motivational states. This theory explains why gamification has traditionally been marginally effective in corporate learning environments, but also shows how companies can fix this problem.

In this article, I address why gamification has enormous potential for L&D, but why current implementations fall short. I also offer specific recommendations for ensuring its viability in the L&D market. To address these issues, I take a psychological and brain science approach. I outline a theory proposed by myself and others (e.g., Higgins, 2000; Maddox, Markman, & Baldwin, 2007; Maddox & Markman, 2010) which argues that the speed and accuracy of task completion depends upon two aspects of motivation: the global motivational state and the local motivational state. When implemented in full, learning accuracy and completion rates can be increased by anywhere from 10% – 40% (Maddox & Markman, 2010).

An Example of Global, Local, Approach, and Avoidance Motivation

To ground these concepts in an example, suppose you are one of several new employees who must complete a number of online training courses as part of your onboarding process. Although you do not have any details about the courses, your (global) motivational state may involve excitement for the new challenge (a global approach motivational state), or it may involve stress or pressure (a global avoidance motivational state).

During the onboarding process, you are provided with the details of each course, and you are informed that you will earn 10 points for each course that you complete. In this case, you are in a local approach motivational state working to earn points for courses completed. These points provide a local motivational state because you now have a specific definition of positive success for completing the course.

This local approach state can be contrasted with a local avoidance motivational state in which you are allocated 10 points for each online course but are informed that you will lose the points if you do not complete the course. Notice that these two cases are mathematically equivalent. If you complete the course you obtain 10 points, and if you do not complete the course you do not obtain 10 points. The critical distinction is in the “framing” of the local incentive. In one case you work to earn an incentive (approach), and in the other case you work to avoid losing an incentive (avoidance).

I explain this further in a recent article, where I reviewed the details of the motivation-effort theory proposed by myself and others (e.g., Higgins, 2000; Maddox, Markman, & Baldwin, 2007; Maddox & Markman, 2010). I briefly review the theory in the table below.

Global and Local Approach-Avoidance

Approach-Avoidance

Current gamification offerings focus exclusively on local approach motivational states, ignoring local avoidance motivational states and global motivation completely. As we show below, focusing exclusively on local approach motivational states, and ignoring the global motivational state likely explains the modest effectiveness of gamification in L&D. This one-size-fits-all approach ignores differences across individuals, job descriptions, and situations. For some individuals, current gamification approaches will increase effort, but for others it will actually reduce effort.

The Need for Motivational Alignment to Improve Gamification

The psychological science literature suggests that when global and local motivation are aligned, cognitive effort is increased. This occurs when the individual has an approach motivated personality, is in a good mood, or is in a positive social situation and earns points for completing online courses. In addition, effort is enhanced when individuals are simultaneously in a global and local avoidance motivational state. This occurs when the learner has an avoidance motivated personality, is in a bad mood, or is in a negative social situation and avoids losing points for completing online courses.

In a previous article, I reviewed the extensive scientific literature that suggests that the human brain has evolved to include two distinct and qualitatively different system of learning. The cognitive skills learning system in the brain is comprised of the prefrontal cortex and medial temporal lobes. It is optimally tuned to learn hard skills such as new software, or the set of steps necessary to complete a task. The cognitive skills learning system relies heavily on working memory and attention, and thus cognitive effort. Performance in the cognitive skills learning system is optimized when the global and local motivation are aligned.

In contrast, the behavioral skills learning system in the brain is comprised of the basal ganglia. It is optimally tuned to learn behavioral skills such as effective interpersonal interaction and leadership. The behavioral skills learning system does not rely on working memory and attention. In fact, there is strong evidence to suggest that too much working memory and attentional allocation leads to “over thinking” and can hinder behavioral skills learning (Maddox, Ashby, Ing, & Pickering, 2004). The behavioral skills learning system instead relies on incremental, dopamine-mediated, real-time feedback learning. Performance in the behavioral skills learning system is optimized when the global and local motivation are misaligned.

The figure below shows the complete motivation-learning framework. Global and local motivational states influence the degree to which working memory and attention are allocated to the learning task. This effectively up or down regulates the involvement of the cognitive skills learning system in the brain which will ultimately affect learning.

Motivation-Learning Hypothesis
Motivation-Learning Hypothesis

Implications of the Motivation-Learning Theory and Recommendations for L&D Practitioners

We at Amalgam recommend that developers continue to embrace gamification in L&D. However, the complete motivation-learning framework must be addressed for gamification to be maximally effective. We offer some suggestions below.

Recommendation 1: L&D practitioners should acknowledge the existence and importance of local avoidance motivational states: Current gamification approaches focus exclusively on local approach motivation. We recommend that L&D developers incorporate both local approach and local avoidance motivational states for broader control over the cognitive effort expended by the learner. If the local approach motivation involves the promise of earning 10 points for completing a training module, then the analogous local avoidance motivation would involve allocating 10 points to the learner before completing the module but informing them that they will lose the 10 points if they do not complete the module. Psychological research suggests that a more effective approach is to link the local motivation directly to a test of the learner’s knowledge of the trained material. Specifically, a local approach motivation can be elicited by asking learners to maximize the number of correct responses on a test, whereas a local avoidance motivation can be elicited by asking learners to minimize the number of errors on a test.

Recommendation 2: L&D practitioners should abandon leaderboards and measure learner’s personality profile instead: A common approach in L&D gamification is to use leaderboards where all learners can compare their learning progress and performance with others. The assumption is that leaderboards bring out the “competitive spirit” in learners and enhance engagement and effort. Extensive research suggests that some individuals view the leaderboard as healthy competition and a welcome challenge (a global approach motivation), whereas others view it as unhealthy stress and pressure (a global avoidance motivation). Notice that when a local approach motivation is implemented (e.g., earn 10 points for completing a learning module), personalities that embrace competition will be in a global and local motivational alignment and will expend more cognitive effort toward learning. On the other hand, personalities that shy away from competition will be in a global and local misalignment and will expend less cognitive effort toward learning. This alone likely explains why current gamification strategies are only modestly effective.

Instead of leaving this to chance, a better approach is to abandon leaderboards, and instead measure the learner’s personality type to determine whether they are approach or avoidance motivated. A straightforward tool for obtaining this information is Higgins’ 11-question Regulatory Focus Questionnaire (RFQ; Higgins, Friedman, Harlow, Idson, Aydak, & Taylor, 2001). The appropriate local motivational state can then be induced for each learner that is aligned with their personality type.

Another method is to focus on the personality type most associated with a particular job description. For example, the majority of individuals in sales have a global approach motivation, whereas most individuals in accounting have a global avoidance motivation. L&D practitioners could more effectively utilize gamification by linking the personality associated with a particular job description with the appropriate local motivational state.

Other methods exist for “overriding” a learner’s personality type and effectively placing them in a global motivational state of the L&D practitioners choosing. These methods are straightforward but are beyond the scope of this article. The interested reader should contact the author.

Recommendation 3: L&D practitioners should acknowledge that cognitive (hard) and behavioral (soft) skills are mediated by different brain systems: The L&D specialist must be cognizant of the nature of the task to be learned. If the task involves hard skills learning then the goal is to increase cognitive effort so that the cognitive skills system is engaged and is highly effective. Combining this approach with something like a microlearning strategy would be even more effective. Under these conditions the global and local motivation should be aligned. Thus, an approach motivated personality should be placed in a local approach motivational state, and an avoidance motivated personality should be placed in a local avoidance motivational state. On the other hand, if the task involves behavioral skills learning (e.g., people skills) then the goal is to decrease cognitive effort so that the behavioral skills system is recruited and dominates learning. Under these conditions the global and local motivation should be misaligned. Thus, an approach motivated personality should be placed in a local avoidance motivational state, and an avoidance motivated personality should be placed in a local approach motivational state.

Closing Remarks

A major strength of this motivation-learning framework is that many aspects of global and local motivation can be manipulated or measured in the workplace. We at Amalgam Insights have the necessary expertise to help companies measure and identify relevant personality types, induce global and local approach and avoidance motivational states, and utilize these effectively to train hard and behavioral skills (such as people skills). Although expertise is required to achieve these aims, the implementation is relatively inexpensive, and is dwarfed by the increase in ROI from enhanced corporate learning. We provide a number of recommendations above to help the L&D practitioner get started.

References

Higgins, E.T. (2000). Making a good decision: Value from fit. American Psychologist, 55, 1217-1230.

Higgins, E.T., Friedman, R.S., Harlow, R.E., Idson, L.C., Ayduk, O.N., & Taylor, A. (2001). Achievement orientations from subjective histories of success: promotion pride versus prevention pride. European Journal of Social Psychology, 31, 2-23.

Maddox, W.T., Ashby, F.G., Ing, A.D., & Pickering, A. (2004). Disrupting feedback processing interferes with rule-based but not information-integration category learning. Memory & Cognition, 32, 582-591.

Maddox, W.T., & Markman, A.B. (2010). The motivation-cognition interface in learning and decision making, Current Directions in Psychological Science, 19, 106-110.

Maddox, W.T., Markman, A.B., & Baldwin, G.C. (2007). Using classification to understand the motivation-learning interface. The Psychology of Learning and Motivation, 47, 213 – 249.

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