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Perception and Attribution in Personality Development
Understanding How We See the World and Attribute Causes - With Special Focus on Agricultural Extension Context
Learning Outcomes
- Understand the perceptual process and factors influencing perception in rural contexts
- Analyze common perceptual errors and their impact on agricultural extension work
- Apply attribution theory to understand farmer behavior and decision-making
- Utilize Kelley's covariation model for accurate causal attributions
- Recognize and mitigate attribution biases in extension practice
- Develop strategies for improving perceptual accuracy in farmer interactions
1. Introduction to Perception
Perception is the process by which individuals organize and interpret their sensory impressions to give meaning to their environment (Robbins & Judge, 2019). It's not merely seeing or hearing; it's the complex psychological process of selecting, organizing, and interpreting sensory data.
Definition: "Perception is the process of receiving information about and making sense of the world around us. It involves deciding which information to notice, how to categorize this information, and how to interpret it within the framework of our existing knowledge" (Luthans, 2011).
Why Perception Matters in Agricultural Extension
In agricultural extension work, perception plays a crucial role in determining the success of technology transfer and adoption. How farmers perceive new technologies, extension workers, and risks significantly influences their decision-making processes.
Two farmers observe the same demonstration plot for a new wheat variety. Farmer A perceives it as an opportunity for higher yields, while Farmer B perceives it as too risky. Their different perceptions lead to completely different adoption decisions, even though they saw the same objective reality.
The Subjectivity of Perception
Perception is highly subjective and personal. What one person perceives in a situation may be completely different from what another person perceives, even when they are exposed to the same stimuli. This subjectivity is influenced by numerous factors including past experiences, cultural background, motivations, and personality.
According to Gibson's Ecological Theory of Perception, perception is an active process where organisms seek out information that is relevant to their goals and needs (Gibson, 1979). In agricultural contexts, farmers actively perceive information that aligns with their farming objectives and risk tolerance.
2. The Perceptual Process (Neisser’s Cyclical Model)
The perceptual process is not linear — it is a continuous cycle. What we perceive changes our expectations, which in turn changes what we attend to next time (Neisser, 1976). This explains why a single negative experience can make a farmer ignore even the best technology in future.
Five Stages of the Perceptual Process
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Environmental Stimuli
Everything present in the environment — demonstration plot, weather, market prices, extension worker’s advice, fellow farmers’ practices, etc.
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Attention & Selection
The farmer notices only what matches his current needs, motives, and past experiences.
Example: A farmer who once suffered heavy loss from hybrid seeds will automatically ignore new hybrid varieties even when they are better. -
Organization
The selected information is arranged into meaningful patterns using Gestalt principles (proximity, similarity, closure, continuity, figure-ground).
-
Interpretation
The farmer assigns meaning based on his past experiences, beliefs, culture, and expectations.
-
Response & Schema Modification
The farmer adopts or rejects the technology. This response updates his mental model (schema), which will influence what he pays attention to the next time he encounters similar stimuli — completing the cycle.
Key Insight: A farmer who once lost money on hybrid seeds (Response) modifies his schema → next time he sees a new variety (Stimuli), he automatically ignores it (Attention) even if it’s better. This is why one failure can block adoption for years.
Perceptual Organization Principles (Gestalt Laws)
During the Organization stage, our brain uses these automatic rules:
| Principle | Description | Agricultural Example |
|---|---|---|
| Figure-Ground | Separates object from background | Pest damage stands out against green leaves |
| Similarity | Similar items grouped | All organic methods seen as one category |
| Proximity | Nearby items grouped | Neighboring farmers using drip = trend |
| Closure | Fills missing gaps | Assumes full knowledge from partial demo |
| Continuity | Prefers smooth lines | Eyes follow aligned crop rows naturally |
Source: Neisser, U. (1976). Cognition and Reality: Principles and Implications of Cognitive Psychology. W.H. Freeman.
3. Factors Influencing Perception
Multiple factors influence how we perceive situations, people, and information. These can be categorized into three main groups: factors in the perceiver, factors in the target, and factors in the situation.
Factors in the Perceiver
These are characteristics of the individual who is perceiving:
| Factor | Description | Extension Example |
|---|---|---|
| Attitudes | Established ways of thinking influence what we notice | A farmer with positive attitudes toward innovation more readily perceives benefits of new technology |
| Motives | Unsatisfied needs or desires stimulate perception | A farmer needing immediate income perceives short-duration crops more favorably |
| Expectations | Anticipations shape what we perceive | Expecting poor results from a demonstration affects actual perception of outcomes |
| Past Experiences | Previous encounters shape current perceptions | Previous failure with a technology creates negative perception of similar technologies |
| Personality | Individual personality traits affect perception | Risk-averse farmers perceive more threats in new practices |
| Cultural Background | Culturally shaped values and beliefs influence perception | Cultural beliefs about natural farming affect perception of chemical inputs |
Factors in the Target
Characteristics of what or who is being perceived:
| Factor | Description | Extension Example |
|---|---|---|
| Novelty | New or unusual elements attract attention | A dramatically different farming method stands out more |
| Motion | Moving objects draw more attention | Dynamic demonstrations are more noticeable than static displays |
| Sounds | Loud or unusual sounds attract attention | Audio-visual aids in training capture more attention |
| Size | Larger objects are more noticeable | Larger demonstration plots attract more attention |
| Background | Context affects perception of target | The same technology presented in different contexts is perceived differently |
| Proximity | Physical or psychological closeness affects perception | Technologies used by neighboring farmers are perceived more favorably |
Factors in the Situation
Environmental context in which perception occurs:
| Factor | Description | Extension Example |
|---|---|---|
| Time | When we see something affects perception | Information received during crisis is perceived differently |
| Work Setting | Physical environment influences perception | Formal office setting vs. informal field setting affects farmer perceptions |
| Social Setting | Social context shapes perception | Individual vs. group settings affect how information is perceived |
| Cultural Context | Cultural norms influence acceptable perceptions | Community norms affect perception of women extension workers |
Research Insight: A study by Rogers (2003) on diffusion of innovations found that how farmers perceive the relative advantage, compatibility, complexity, trialability, and observability of new technologies significantly influences adoption rates, highlighting the critical role of perception in agricultural extension.
4. Perceptual Errors in Extension Work
Perceptual errors are systematic distortions that occur in the perceptual process. Understanding these errors helps extension workers avoid misjudgments and improve communication with farmers.
Selective Perception
The tendency to selectively interpret what we see based on our interests, background, experience, and attitudes.
An extension worker focused on yield improvement might selectively perceive yield data from a demonstration plot while overlooking soil health indicators that a soil scientist would notice immediately.
Halo Effect
Drawing a general impression about an individual or situation based on a single characteristic.
A farmer who successfully adopted one technology is perceived as "progressive" across all domains, leading extension workers to overestimate their willingness to adopt other new practices.
Contrast Effects
Evaluation of a person or situation in contrast to other recent encounters with similar persons or situations.
After visiting a highly successful progressive farmer, an average farmer's practices might be perceived more negatively than they would be if evaluated independently.
Projection
Attributing one's own characteristics to other people.
An extension worker from an urban background might project their own values and risk perceptions onto farmers, assuming they share similar attitudes toward technology adoption.
Stereotyping
Judging someone based on our perception of the group to which that person belongs.
Assuming that all smallholder farmers are risk-averse or that all women farmers are only interested in kitchen gardening, without considering individual differences.
Self-Fulfilling Prophecy (Pygmalion Effect)
A situation in which our expectations about people affect our interaction with them in such a way that those expectations are fulfilled.
An extension worker who expects certain farmers to be uncooperative might interact with them differently, actually causing them to become uncooperative.
Theoretical Note: These perceptual errors are well-documented in organizational behavior literature. The halo effect was first described by Thorndike (1920), while stereotyping has been extensively studied in social psychology, particularly by Hamilton (1981).
5. Attribution Theory Foundations
Attribution theory is concerned with how individuals interpret events and how this relates to their thinking and behavior. It deals with the "why" questions people ask when something happens.
Fritz Heider: The Founder of Attribution Theory
Fritz Heider (1958) is considered the founder of attribution theory. In his book "The Psychology of Interpersonal Relations," he proposed that people are naive psychologists trying to make sense of the social world. He distinguished between:
Internal Attribution
- Attributing behavior to personal characteristics
- "The farmer failed because he's lazy"
- Also called dispositional attribution
External Attribution
- Attributing behavior to situational factors
- "The farmer failed because of drought"
- Also called situational attribution
Heider's Common Sense Psychology
Heider argued that people naturally develop explanations for why things happen. These explanations help them understand, predict, and control their environment. In agricultural contexts, these attributions significantly influence future behavior and technology adoption.
When a new crop variety fails, farmers might attribute the failure internally ("I didn't manage it properly") or externally ("The seeds were bad" or "The weather was unfavorable"). These attributions will influence whether they try the variety again.
Correspondent Inference Theory (Jones & Davis, 1965)
This theory explains how we infer that a person's behavior corresponds to an underlying disposition or personality trait. We are more likely to make internal attributions when:
- Behavior is freely chosen
- Behavior produces non-common effects (unique outcomes)
- Behavior is low in social desirability
Historical Context: Heider's work emerged from Gestalt psychology traditions and was influenced by Kurt Lewin's field theory. His 1958 book laid the foundation for decades of attribution research that followed.
6. Weiner's Attribution Model
Bernard Weiner (1972, 1985) developed a comprehensive theory of attribution that focused on achievement contexts. His model has particular relevance for understanding farmer responses to success and failure in agricultural endeavors.
Weiner's Three-Dimensional Model
Weiner proposed that attributions can be classified along three dimensions:
| Dimension | Categories | Description | Agricultural Example |
|---|---|---|---|
| Locus of Control | Internal vs. External | Whether the cause is inside or outside the person | Farmer's skill (internal) vs. Weather conditions (external) |
| Stability | Stable vs. Unstable | Whether the cause is permanent or temporary | Soil quality (stable) vs. Pest outbreak (unstable) |
| Controllability | Controllable vs. Uncontrollable | Whether the cause can be controlled by the person | Irrigation timing (controllable) vs. Hailstorm (uncontrollable) |
Impact on Future Expectations and Behavior
According to Weiner, the specific attribution made for success or failure influences:
- Expectations for future success: Stable attributions lead to similar expectations
- Emotional responses: Different attributions evoke different emotions
- Future behavior: Attributions influence motivation and effort
A farmer who attributes crop failure to unstable, external, uncontrollable causes (bad weather) is likely to maintain motivation and try again. However, if the failure is attributed to stable, internal, uncontrollable causes (lack of farming ability), the farmer may develop learned helplessness and reduce future efforts.
Emotional Consequences of Attributions
Weiner's research identified specific emotional responses associated with different attributions:
| Attribution Pattern | Emotional Response to Success | Emotional Response to Failure |
|---|---|---|
| Internal + Stable | Pride, confidence | Shame, humiliation |
| Internal + Unstable | Thankfulness, relief | Guilt, self-blame |
| External + Stable | Gratitude | Anger, frustration |
| External + Unstable | Surprise | Surprise, shock |
Research Application: Weiner's model has been extensively applied in educational psychology and has significant implications for agricultural extension, particularly in understanding farmer responses to success and failure with new technologies (Weiner, 1985).
7. Kelley's Covariation Model
Harold Kelley's (1967, 1973) covariation model is one of the most influential attribution theories. It proposes that people attribute behavior to causes that are present when the behavior occurs and absent when it doesn't occur.
The Covariation Principle
Kelley suggested that people use the principle of covariation: an effect is attributed to one of its possible causes with which, over time, it covaries. We look for three types of information:
Kelley's Three Dimensions of Information
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Consensus
Do other people behave similarly in this situation? (High vs. Low)
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Distinctiveness
Does the person behave similarly in different situations? (High vs. Low)
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Consistency
Does the person behave similarly in this situation over time? (High vs. Low)
Attribution Patterns in Kelley's Model
Different combinations of consensus, distinctiveness, and consistency information lead to different attributions:
| Information Pattern | Attribution | Agricultural Example |
|---|---|---|
| Low Consensus, Low Distinctiveness, High Consistency | Internal Attribution (to the person) | Only this farmer has problems with this crop (low consensus), has problems with other crops too (low distinctiveness), and has consistent problems over time (high consistency) → Attribution to farmer's ability/methods |
| High Consensus, High Distinctiveness, High Consistency | External Attribution (to the stimulus) | Many farmers have problems with this crop (high consensus), this farmer has no problems with other crops (high distinctiveness), and problems are consistent over time (high consistency) → Attribution to crop characteristics |
| Low Consensus, High Distinctiveness, Low Consistency | External Attribution (to circumstances) | Only this farmer has problems (low consensus), only with this crop (high distinctiveness), and problems are inconsistent (low consistency) → Attribution to unusual circumstances |
An extension worker trying to understand why a particular farmer is having poor yields with a new rice variety would gather information about:
Consensus: Are other farmers also having problems with this variety?
Distinctiveness: Is this farmer having problems with other crops too?
Consistency: Has this been a consistent problem across seasons?
The pattern of answers would guide whether to attribute the problem to the farmer, the variety, or specific circumstances.
Multiple Necessary Causes Schema
Kelley also proposed that for some effects, we assume multiple causes are necessary. In agriculture, this is particularly relevant as crop success or failure typically involves multiple factors working together.
Theoretical Significance: Kelley's model represents a sophisticated information-processing approach to attribution that has generated substantial research. His 1967 paper "Attribution Theory in Social Psychology" is considered a landmark publication in social psychology.
8. Attribution Biases and Errors
While attribution theories describe how people should make attributions rationally, research shows that people systematically deviate from these rational models due to various cognitive biases.
Fundamental Attribution Error
The tendency to overestimate internal factors and underestimate external factors when explaining others' behavior.
An extension worker observes a farmer rejecting a new technology and attributes this to the farmer's "conservatism" or "resistance to change" (internal attribution), while overlooking external factors like lack of credit access, unsuitable soil conditions, or previous negative experiences with similar technologies.
Actor-Observer Bias
The tendency to attribute our own behavior to external causes while attributing others' behavior to internal causes.
When an extension program fails, the extension worker might attribute it to external factors like "uncooperative farmers" or "bad weather" (external attribution for self), but when a farmer's individual enterprise fails, attribute it to the farmer's "poor management" (internal attribution for others).
Self-Serving Bias
The tendency to attribute successes to internal factors and failures to external factors.
A farmer attributes successful crop yield to their "skill and hard work" (internal) but attributes crop failure to "poor quality seeds" or "unfavorable weather" (external). Similarly, extension workers might take credit for successful programs but blame external factors for unsuccessful ones.
Ultimate Attribution Error
Extension of fundamental attribution error to group contexts - attributing negative behavior of outgroup members to internal dispositions while explaining away similar behavior by ingroup members.
When farmers from a different community reject a technology, it's attributed to their "backwardness" (internal), but when farmers from one's own working area reject it, it's attributed to "communication problems" or "implementation issues" (external).
False Consensus Effect
The tendency to overestimate the extent to which others share our beliefs, attitudes, and behaviors.
An extension worker who values scientific farming methods might overestimate how many farmers share this value, leading to surprise and frustration when farmers prefer traditional methods.
Counterfactual Thinking
Imagining alternatives to past events - "if only" thinking that can affect attributions and emotional responses.
After crop failure, a farmer thinks "If only I had irrigated one day earlier," leading to self-blame and internal attribution, even if the actual cause was external.
Research Foundation: These biases were systematically documented by Ross (1977) in his seminal paper "The Intuitive Psychologist and His Shortcomings." The fundamental attribution error has been replicated across cultures, though it manifests differently in collectivistic versus individualistic cultures (Miller, 1984).
9. Agricultural Case Studies
Real-life case studies from Indian agricultural context illustrate how perception and attribution processes operate in extension work and farmer decision-making.
Situation: In a Bihar village, an extension worker observed that farmer Rajesh consistently arrived late to training sessions and seemed disengaged. The worker attributed this to laziness and lack of interest (internal attribution).
Reality: Further investigation revealed that Rajesh had elderly parents requiring morning care, his farm was 3km from the training location, and he had negative past experiences with similar programs that promised much but delivered little.
Attribution Error: Fundamental attribution error - overlooking situational constraints.
Resolution: When the extension worker adjusted training timing and provided concrete evidence of program benefits, Rajesh became one of the most active participants.
Situation: A women's self-help group in Tamil Nadu achieved remarkable success with vegetable cultivation where previous (male) farmers had failed. Male community members attributed this to "luck" or "easy market conditions" (external attribution for others' success).
Reality: The women's group had systematically implemented proper spacing, regular irrigation, integrated pest management, and developed direct market linkages - factors the male farmers had overlooked.
Attribution Error: Ultimate attribution error - explaining away outgroup success.
Resolution: When the systematic approach was documented and shared, perceptions changed, leading to wider adoption of their methods.
Situation: A high-profile demonstration plot for a new wheat variety in Punjab showed poor results. Farmers attributed the failure to "poor quality seeds" (external attribution), while the seed company attributed it to "farmer mismanagement" (internal attribution).
Reality: Application of Kelley's covariation model revealed: High consensus (many farmers had problems), high distinctiveness (only this variety had problems), high consistency (problems across regions) → pointing to variety characteristics as the cause.
Attribution Process: Proper use of covariation information led to accurate attribution.
Resolution: The variety was withdrawn and replaced with a more suitable one, restoring farmer trust.
Situation: In a water-scarce region of Maharashtra, only a few farmers adopted drip irrigation despite substantial subsidies. Extension workers attributed low adoption to farmer "conservatism" and "risk aversion."
Reality: Farmers perceived the technology as complex, requiring specialized knowledge they lacked. They also doubted the promised water savings based on neighbors' mixed results.
Perceptual Issue: Selective perception - extension workers focused on economic benefits while farmers focused on complexity and reliability.
Resolution: When demonstration included hands-on training and realistic water saving measurements, adoption increased significantly.
Situation: Extension workers introduced soybean cultivation to tribal farmers in Odisha, assuming they would perceive it as economically beneficial. The initiative failed despite good technical support.
Reality: Tribal farmers perceived soybean as disrupting their traditional food systems and cultural practices. Their attribution: "outsiders trying to change our way of life" rather than "opportunity for income."
Perceptual Gap: Contrast between extension workers' economic perception and farmers' cultural perception.
Resolution: Subsequent programs integrated new crops within traditional systems, showing respect for cultural values while introducing economic benefits.
Situation: In 2018–2020, an NGO introduced high-yielding hybrid maize varieties to smallholder farmers in Siaya and Kakamega counties, Kenya, with free seeds and training. Adoption remained below 15 % despite proven 30–40 % yield gains in on-farm trials.
Reality: Farmers perceived the hybrids negatively on three cultural dimensions: (a) the flour makes stiff ugali that “does not feel right in the stomach” (taste/texture inferior to local varieties), (b) the crop cannot be used for traditional beer brewing during funerals and ceremonies, and (c) surplus grain cannot be easily stored in traditional granaries because hybrids are more susceptible to weevils.
Perceptual Gap: Extension agents focused only on economic and yield advantages (economic perception), while farmers evaluated the technology through deep cultural and social lenses (identity and ritual perception).
Attribution by farmers: “These seeds are for rich people who eat in hotels; they are not for Luhya people.”
Resolution: A follow-up project co-developed with women’s groups introduced dual-purpose hybrids suitable for both ugali and local brewing, plus low-cost hermetic storage bags. Adoption rose to 68 % within two seasons.
Source: Fischer et al. (2021), “Beyond yield: cultural compatibility and maize variety choice in western Kenya”, Food Security.
Situation: Between 2005–2010, a FAO project promoted zero-tillage for quinoa and potato in the Andean communities of Bolivia to combat soil erosion. Initial adoption was near zero; many farmers openly rejected the practice.
Reality: Aymara farmers perceived zero-tillage as violating Pachamama (Mother Earth). Traditional belief requires the soil to be “opened” and “breathed” each season as a ritual offering; leaving crop residue on the surface was seen as “leaving the field undressed and ashamed”.
Perceptual Gap: Technicians saw residue as “mulch for moisture conservation” (scientific perception); farmers saw it as disrespect to the earth spirit (spiritual perception).
Attribution by farmers: “If we don’t turn the soil, Pachamama will be angry and withhold her fertility.”
Resolution: The project team worked with yatiris (local spiritual leaders) to create a modified ritual that “dressed” the field with residue while still symbolically “opening” a small patch. After ritual integration, adoption reached 72 % and soil erosion dropped dramatically.
Source: Swinton et al. (2018), “Integrating cosmology and conservation: zero-tillage among Aymara farmers”, World Development.
10. Practical Guidelines for Extension Workers
Based on understanding of perception and attribution processes, extension workers can adopt specific strategies to improve communication and technology adoption.
Do's for Better Perception Management
- Check your own perceptions regularly - are you making attribution errors?
- Gather multiple perspectives before forming judgments about farmer behavior
- Use Kelley's covariation model systematically for important decisions
- Provide clear, consistent information to reduce perceptual distortions
- Create opportunities for farmers to experience technologies firsthand
- Consider cultural and contextual factors in farmer perceptions
- Use multiple communication channels to reinforce messages
- Encourage farmer-to-farmer communication to build trust
Don'ts to Avoid Perceptual Pitfalls
- Don't jump to conclusions based on limited information
- Avoid stereotyping farmers based on age, gender, or landholding
- Don't assume your perceptions are universally shared
- Avoid fundamental attribution error - consider situational factors
- Don't dismiss farmer concerns as "resistance to change"
- Avoid self-serving bias in evaluating program success/failure
- Don't rely solely on your own perspective - seek feedback
- Avoid false consensus - check what farmers actually think
Strategies for Accurate Attribution
- Systematic Information Gathering: Use Kelley's model - collect consensus, distinctiveness, and consistency information
- Consider Multiple Causes: Agricultural outcomes usually have multiple causes - avoid single-cause explanations
- Check Your Biases: Regularly reflect on whether you're making fundamental attribution error or self-serving bias
- Seek Disconfirming Evidence: Actively look for information that challenges your initial attributions
- Cultural Sensitivity: Understand how cultural factors influence attribution patterns in different communities
Improving Farmer Perceptions of Innovations
Steps to Enhance Positive Perception
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Demonstrate Relative Advantage
Clearly show how the innovation is better than current practices
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Ensure Compatibility
Align innovations with existing values, experiences, and needs
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Reduce Complexity
Make technologies easy to understand and use
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Provide Trialability
Allow farmers to experiment on a small scale first
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Enhance Observability
Make results visible and measurable
11. Key Takeaways
Essential Insights on Perception and Attribution
- Perception is subjective: Different people perceive the same reality differently based on their experiences, beliefs, and context
- Multiple factors influence perception: Characteristics of the perceiver, target, and situation all shape how we see the world
- Perceptual errors are systematic: Selective perception, halo effect, stereotyping, and other errors consistently distort our perceptions
- Attributions guide behavior: How we explain causes of events (internal vs. external) significantly influences future actions and emotions
- Kelley's model provides systematic approach: Consensus, distinctiveness, and consistency information help make accurate attributions
- Attribution biases are pervasive: Fundamental attribution error, self-serving bias, and other biases routinely affect our judgments
- Cultural context matters: Attribution patterns vary across cultures, affecting technology adoption and extension effectiveness
- Self-awareness improves practice: Recognizing our own perceptual and attribution biases is the first step toward more effective extension work
Practical Applications for Extension Professionals
- Use systematic approaches rather than intuitive judgments for important decisions
- Regularly check for and correct perceptual errors and attribution biases
- Consider multiple perspectives before forming conclusions about farmer behavior
- Adapt communication strategies to account for different perceptual frameworks
- Create environments that support accurate perception and attribution
- Develop cultural competence to work effectively across different communities
12. References
Academic References
- Fiske, S. T., & Taylor, S. E. (2017). Social cognition: From brains to culture. Sage publications.
- Gibson, J. J. (1979). The ecological approach to visual perception. Houghton Mifflin.
- Hamilton, D. L. (1981). Cognitive processes in stereotyping and intergroup behavior. Psychology Press.
- Heider, F. (1958). The psychology of interpersonal relations. John Wiley & Sons.
- Jones, E. E., & Davis, K. E. (1965). From acts to dispositions: The attribution process in person perception. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 2, pp. 219-266). Academic Press.
- Kelley, H. H. (1967). Attribution theory in social psychology. In D. Levine (Ed.), Nebraska symposium on motivation (Vol. 15, pp. 192-238). University of Nebraska Press.
- Kelley, H. H. (1973). The processes of causal attribution. American Psychologist, 28(2), 107-128.
- Luthans, F. (2011). Organizational behavior: An evidence-based approach. McGraw-Hill.
- Miller, J. G. (1984). Culture and the development of everyday social explanation. Journal of Personality and Social Psychology, 46(5), 961-978.
- Neisser, U. (1976). Cognition and reality: Principles and implications of cognitive psychology. WH Freeman.
- Robbins, S. P., & Judge, T. A. (2019). Organizational behavior. Pearson.
- Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
- Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 10, pp. 173-220). Academic Press.
- Thorndike, E. L. (1920). A constant error in psychological ratings. Journal of Applied Psychology, 4(1), 25-29.
- Weiner, B. (1972). Theories of motivation: From mechanism to cognition. Markham.
- Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548-573.
Agricultural Extension References
- Chambers, R., Pacey, A., & Thrupp, L. A. (Eds.). (2020). Farmer first: Farmer innovation and agricultural research. Routledge.
- Leeuwis, C., & Van den Ban, A. (2004). Communication for rural innovation: Rethinking agricultural extension. Blackwell Science.
- R├╢ling, N. G., & Wagemakers, M. A. (Eds.). (2012). Facilitating sustainable agriculture: Participatory learning and adaptive management in times of environmental uncertainty. Cambridge University Press.
- Scarborough, V., Killough, S., Johnson, D. A., & Farrington, J. (Eds.). (2013). Farmer-led extension: Concepts and practices. Intermediate Technology Publications.
- Vanclay, F., & Mesiti, L. (2018). Understanding farmer skepticism about agricultural science and technology. In The social contours of risk (pp. 179-198). Routledge.
Note: This comprehensive resource integrates classical psychological theories with practical agricultural extension applications. The concepts covered provide a solid foundation for understanding and improving farmer-extension interactions and technology adoption processes.
"We don't see things as they are, we see them as we are." - Ana├пs Nin
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