A. Specific learning outcomes. At the end of the course students will be able to
- Describe the uses of sensory measurement in psychology, medicine and food science.
- Apply systems analysis models of information processing in the brain, comprising central processing, subroutines for automatic behavior, both motor and cognitive output.
- Describe the minimizing of sensory input through selective attention, sensory adaptation, recoding input and how this affects perception during sensory testing.
- The goals of sensory measurement: Sensory Evaluation I and II, Consumer acceptance and preference testing, Sensory psychophysics
- Appraise how these goals affect experimental design and statistical analysis.
- Classify booth design and review environments for testing.
- Appraise relative advantages and disadvantages of central location, home use, lab testing andfield testing.
- Assess interactions with judges: oral, written, computer, other non-written methods.
- Describe experimenter effects on judge performance.
- Illustrate the use and pitfalls of using two, three, four digit random numbers with examples of lucky and unlucky numbers in other cultures.
- Evaluate other methods of judge-experimenter communication.
- Classify forced-choice difference tests, specified and unspecified.
- Describe response bias, tau and beta criteria.
- Compare forced-choice versus signal detection solutions to criterion variation and their applications within Sensory I and Sensory II.
- Describe and discuss why same-different and A Not-A tests need a signal detection analysis.
- Describe central processing for difference tests.
- Explain Thurstonian modeling, decision rules and cognitive strategies.
- Evaluate and appraise the application of Thurstonian modeling to forced-choice tests.
- Describe measures of difference: d′, R-Index and the confirmation of d′ tables.
- Identify applications in industry.
- Describe statistical power of tests.
- Illustrate why the tetrad is more powerful than the triangle.
- Assess and evaluate the new self-specification tests.
- Demonstrate why the self-specified 2-AFC is more powerful than the tetrad.
- Describe significance testing for d′ using B values.
- Analyze the experimental variables affecting test power and how this can be applied in the food industry.
- Describe for difference tests, the clarity of signals reaching the central processor, sequence effects, adaptation and response bias.
- Describe priming and its use
- Devise Sequential Sensitivity Analysis explanations of variation in d′, caused by sequence and memory effects.
- Explain why the 2-AFC delivers the highest d′ values which can elicit greater operational power than the 3-AFC.
- Describe the neural mechanisms of remembering and forgetting as well as memory distortion and the effects of interstimulus time intervals.
- Use and apply priming.
- Evaluate and contrast DTM vs duo-trio superiority.
- Evaluate and compare which is the most powerful, sensitive and suitable difference test for Sensory Evaluation I and II.
- Illustrate and use warm-up and bilateral tasting.
- Discuss the applications of preference testing, test vs operational preferences and explain why the ‘No Preference’ response option is essential.
- Indicate legal aspects of advertising claims.
- Explain misunderstandings of ‘No Preference’ results and asymmetric dominance.
- Evaluate misunderstandings in the literature.
- Apply chi-squared significance testing using ‘placebo’ and ‘test’ pairs.
- Describe the use of placebo pairs for statistical analysis or screening.
- Describe liking, choosing and buying preferences, alternating and 50:50 no preference.
- Appraise and contrast detection vs rejection thresholds.
- Assess the use of cognitive subroutine theory to solve the problem of placebo preferences vs response bias explanations
- Describe how the reverse hidden demand characteristics test and the tetrad preference test eliminate placebo preference problems.
- Summarize and construct measures of validity and the setting up of ‘take away’ preferences.
- Describe and discuss the monitoring of consumer buying behavior and the effects of engaging the consumer.
- Appraise and assess how difference tests and preference tests fit Sensory Evaluation I and II and Consumer acceptance conditions and predictions.
- Illustrate sampling methods and the use of Abbott’s formula as well as the use of estimations of confidence intervals for difference and preference tests.
- Describe Signal Detection Theory, sources of noise and effects of beta criterion variation.
- Describe hits, false alarms, correct rejections and misses for computing d′.
- Use ROC curves and assumption validated computations of d′.
- Describe z-plot ROC curves, asymmetrical ROC curves from non-equal noise and signal+noise distributions.
- Describe the use of ROC curves to determine cognitive strategies.
- Use and apply nonparametric measures from ROC curves: P(A), P(C) and compute P(A) and d′ by Yes-no and rating procedures.
- Describe reasons why Signal Detection Methods are criterion free.
- Apply computation of John Brown’s R-Index by rating and ranking.
- Explain why R-index ≈ P(A).
- Classify the assumptions for the R-Index and why the R-Index is criterion free.
- Apply significance tests for the R-Index.
- Explain the causes of R-Index values less than 50%. 56
- Explain why R-indices by ranking are greater than by rating and relate it to boundary variance.
- Describe context effects for R-Index rating.
- Illustrate and apply the Laws of Psychophysics: Weber’s law, Fechner’s logarithmic law and Stevens’s power law.
- Illustrate the effects of the status of numbers: nominal, ordinal, interval, ratio data and demonstrate their effects on the assumptions for parametric statistics.
- Analyze the uses of scaling.
- Evaluate and assess the cognitive mechanisms used during scaling: absolute vs relative models.
- Describe and discuss how context and memory effects support the relative model for non- expert consumers and how this affects experimental design.
- Use and relate rank-rating vs serial monadic rating designs.
- Describe and identify the causes of nonlinear spacing with numerical scales and its effects on parametric statistics.
- Appraise and illustrate Oppenheim’s warning.
- Describe and discuss unipolar vs bipolar scales, anchoring, labelling, calibration and descriptive analysis scale stabilization.
- Explain and evaluate the fashion for 9-point scales in food sensory science, while discussing the relationship between scale length and the number of stimuli being tested.
- Classify and describe smiley face scales, line scales, time-intensity, temporal dominance of sensations, magnitude estimations and labeled magnitude scales.
- Describe and discuss the use of ranking as an intensity measure.
- Describe how to predict the number of stimuli that can be ranked.
- Describe and assess memory advantages of ranking over rating.
- Describe and assess two-stage ranking and possible applications in Food Science.
- Compare and assess attribute-by-attribute vs serial monadic approaches to descriptive analysis.
- Describe how to compute d′ values from scaling.
- Describe and assess the various uses and abuses of rating scales.
- Categorize and explain the reasons for product acceptance and rejection.
- Describe and assess 9-point hedonic scales, action scales, the LAM and LIM scales, purchase- intent scales and quality scales.
- Describe just-about-right scales and discuss Johnson and Vickers’s correction.
- Describe and assess validity measures for the 9-point hedonic scale.
- Develop a critical examination of the traditional 9-point scale, summarizing derived measures and analyses.
- Assess experimental evidence showing the ‘words only’ and ‘numbers only’ versions of the 9- point hedonic scale are not interchangeable.
- Describe the use of the ‘numbers only’ version for comparison with market leaders and losers and the use of histograms for the ‘words only’ version.
- Describe and assess hedonic ranking with an R-Index analysis, the computation of RJB vs RMAT, the related significance tests and their applications in industry.
- Describe and discuss its advantages over 9-point hedonic scale: within-category preferences, cross-cultural measures and range stabilization.
- Identify and describe the experimental basics of descriptive analysis. 57
- Describe and assess commercial methods: Flavor Profile, Texture Profile, Spectrum Method, QDA, QFP, PAA.
- Describe and explain dumping.
- Explain and evaluate the QDA claim to be Sensory Evaluation II controversy.
- Describe the adoption of rank-rating for QFP and the development of contextual standards in a DIY experimental design.
- Argue the importance of good panel management.
- Classify and describe Free Choice Profiling, Flash Profiling, Multidimensional Scaling, Napping and other sorting tasks.
- Describe concept formation mechanisms: abstraction and generalization as well as the importance of concept alignment for descriptive analysis.
- Describe the use of the R-Index for measuring abstract concepts and its applications in quality control.
- Describe concept drift and assess its experimental consequences and its stabilization by multiple standards, while also assessing implications for descriptive analysis.
- Describe R-Index measurement’s application to storage studies, quality control and the measurement of abstract consumer concepts, while predicting its applications in marketing.
- Describe ad hoc vs permanent concepts.
- Describe the semantic differential and the repertory grid.
- Categorize and appraise descriptive analysis time-savers.
- Describe and explain consumer language, everyday, lexical and scientific language and their uses in Sensory Evaluation I and II, Consumer Acceptance and Preference measures as well as Psychophysics.
- Describe the Lee Whorf hypothesis and experiments it generated.
- Describe cross-cultural studies in vision and taste.
- Describe and assess the myth of basic tastes in Psychophysics and its consequences in experimental design.
- Describe and assess Malay qualifying phrases
- Describe and discuss the derivation and measurement of the umami taste concept.
- Assess evidence that the sour-bitter confusion is linguistic, and evaluate the Mexican Spanish ‘agrio’ problem and second language effects.
- Evaluate the source of taste confusions and describe the relevant experiments with children.
- Compare suggestion and hidden demand effects.
- Describe and interpret taste and smell suggestion effects, the Granada experiment and ‘transmitting’ smell over television.
- Describe and assess experiments discrediting the use of primary taste profiling in taste psychophysics.
- Evaluate the idea of four, five or many primary tastes, taking into account the history of primary tastes and the status of the evidence for and against primary tastes.
- Describe suggestion effects with scaling and evaluate their dangers for consumer acceptance testing and its avoidance
- Describe the design of psychological questionnaire measures and their validation, so as to assess standard questionnaire measures of emotion.
- Describe face validity.
- Describe why clinical psychological measures of emotion can be misleading for the choice of labels in a questionnaire regarding non-cognitive motivations for purchasing products.
- Describe and assess King and Meiselman’s Emotion questionnaire and describe some applications.
- Describe and discuss Russell’s model of underlying dimensions of emotional experience.
- Describe and discuss the use of pictures for measuring emotional reaction to products, including PrEmo face scales and Adrient Technologies’s use of multi-pictorial boards.
- Assess impulse buying and Ditmar and Bond’s model of identity expression.
- Describe habit breaking and evaluate fast thinking and the ICA vegetable selling experiment.
- Describe Lieberman’s fMRI work on the medial pre-frontal cortex, its potential for consumer purchase intent and assess other physical possibilities for extracting the same information: EEG, GSR, heart rate, skin temperature, blood flow, hypnosis.
- Describe and discuss the reading of facial expressions: Ekman’s F.A.C.E. training, Hill’s Sensory Logic and the Noldus and Realeyes computer measures.
- Describe Landscape Segmentation Analysis (LSA) as a product optimization exercise and its applications in comparison with preference mapping.
- Explain triangulation and unfolding, yielding products maps derived from hedonic measures.
- Describe and explain the use of map fitting rather than correlation, to fit attributes from descriptive analysis to the LSA map, in response to inverted U-shaped hedonic functions.
- Describe demographic group formation with LSA and how such groups are mixed in terms of the traditional categories.
- Describe Optimum Portfolio Placement and its use.
- Describe and discuss the effects of inadequate measurement on the LSA map.
- Describe and assess the above sensory tests and using knowledge of the relevant sensory mechanisms and information processing in the brain, justify the development of methods that are compatible with the judge’s sensory function for the particular product under consideration.
How this course addresses IFT core competencies
The course is a senior level course taught in the Fall quarter. FST 107 is a 4-unit course consisting of one 3-hour lecture per week with associated weekly 3-hour laboratory classes which address measurement techniques and the testing of models taught in the classes. These must be written up twice each week: firstly using the rules for a professional academic journal, secondly as a memo to the boss in a commercial company. Besides the TA 1-hour office hours session, the instructor runs a 9am -11pm phone service office hours 7-days a week. This allows students to phone in when they are having difficulties with the course.
B. Tools used to assess program outcomes
Every week two reports are required for each week’s laboratory classes, as mentioned above.. Each week, they are given quizzes in class to test their understanding of the topics taught the week before. A three hour final exam features questions from the whole of the quarter.
Bloom’s levels I-VI
C. Brief summary of assessments to date
This course uses a course manual of pictures, diagrams and notes. The goal of the course is to introduce students not only to the available sensory tests but also the workings of the senses and how the brain processes information during these tests. This can be used to explain why some tests are more efficient than others The goal is to begin to give the students sufficient understanding of the workings of the brain and senses so that they can critically review sensory research methods in the literature and industry and custom-design their own methods to fit their products and experimental limitations. Each year students are required to complete a course evaluation and encouraged to give their opinions of the course and suggest improvements during discussion. This provides useful information for the yearly course revision, for improving the teaching and including up-to-date information in the syllabus. Course assessments have always been good but we can always do better. The course has sometimes also been given to companies/universities in USA, Canada Latin America, Asia, Europe, Australasia, which can also give insights into course revisions.