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Ph.D. Program Course Descriptions and Objectives
Course Descriptions:
Computer-Assisted Data Management and Analysis (PSYC 604)
Research and Inferential Statistics (PSYC 605)
Measurement Theory (PSYC 606)
Multivariate Statistical Analysis (PSYC 608)
Assessment and Public Policy (PSYC 770)
Assessment Methods and Instrument Design (PSYC 812)
Performance Assessment (PSYC 814)
Classical Test Theory and Generalizability Theory (PSYC 816)
Structural Equation Modeling (PSYC 830)
Item Response Theory (PSYC 832)
Computers in Testing (PSYC 834)
Hierarchical Linear Models (PSYC 836)
Special Topics in Assessment (PSYC 850)
Assessment Consultation and Practice (PSYC 855)
Doctoral Assessment Practicum (PSYC 878)
Developmental Psychology (PSYC 614 or 616)
Cognitive Psychology (PSYC 613)
Social Psychology (PSYC 616)
Qualitative Research (PSYC 840)
Competencies:
Psychology Foundations
Technology Competencies
Computer-Assisted Data Management
and Analysis (PSYC 604)
(Prerequisite: Permission of
instructor)
Students who have taken this course should be able to:
- Construct a graph in Excel.
- Create a spreadsheet in Excel that performs calculations.
- Transfer data across different software packages (SPSS,
SAS, Excel, Microsoft Word).
- Screen data in both SPSS and SAS.
- Identify missing data in both SPSS and SAS.
- Compute variables and recode data in both SPSS
and SAS.
- Conduct data transformations on a subset
of the data in both SPSS and SAS.
- Analyze subsets of the data in both SPSS
and SAS.
- Merge and concatenate files in both SPSS
and SAS.
- Conduct and interpret basic inferential
statistics in both SPSS and SAS.
- Identify and correct errors in both
SPSS and SAS
Research and Inferential
Statistics (PSYC 605)
Provides an understanding of types of research, inferential
statistics, research-report development, research methodology
and implementation, program evaluation, needs assessment,
and ethical and legal considerations. (Prerequisite:
PSYC 600 or equivalent; or admission into the Assessment & Measurement Ph.D. program or Psychological Sciences M.A. program.)
Students who have taken this
course should be able to:
- Distinguish among descriptive,
relational, experimental, and quasi-experimental research
methods.
- Explain the logic underlying statistical hypothesis
testing.
- Explain the importance of sampling distributions
in hypothesis testing.
- Distinguish between significance tests and
effect sizes.
- Calculate and interpret Pearson correlation
coefficients.
- Calculate and interpret simple linear regression
equations.
- Explain the logic underlying analysis
of variance.
- Explain the statistical assumptions
underlying ANOVA and the ANOVA model's
robustness
to their violation.
- Distinguish between planned and post
hoc ANOVA comparisons.
- Construct a planned comparison
and test it for significance.
- Test a set of post hoc comparisons
for significance.
- Explain statistical power and
its influences.
- Conduct a power analysis
for one-factor experimental
designs
to choose
an appropriate sample size.
- Interpret interaction effects
in factorial ANOVA designs.
- Perform tests of simple
effects to follow up
significant interactions.
- Identify an effective
blocking variable
and analyze the
data from a treatments
by blocks
ANOVA design.
- Identify an effective
covariate and analyze
the data from
a one-factor analysis
of covariance design.
- Use SPSS to analyze
data from one-
or two-factor ANOVA
designs
containing
between-subjects
factors, within-subjects
factors, or both.
- Differentiate between
internal and
external validity of
experimental
designs.
- Interpret the
findings from
basic quasi-experimental
designs.
- Explain the ethical
and legal issues
involved in
research with human
subjects.
- Identify a
research
topic, conduct
a brief review
of the literature,
and develop
a
proposal
for future research.
Measurement
Theory (PSYC 606)
Advanced
measurement applications of classical test score theory,
generalizability measurement theory, scale
construction concepts, test bias, standard setting
techniques and
item response theory. (Prerequisites: PSYC 605).
Students who have taken this
course should be able to:
- Define and describe differences among evaluation, assessment,
research, and measurement.
- Define measurement and statistical terms and concepts.
- Describe scaling, the process of test construction,
and test scores as composites.
- Interpret the following scales and transformed scores:
T scores, Z scores, stanines, IRT ability estimates,
and grade and age equivalent scores.
- Explain
test results using norm-referenced and criterion-referenced
interpretations.
- Identify various item formats for achievement,
attitude, and behavioral instruments.
- Describe the Classical
True Score model and associated reliability estimation
procedures.
- Interpret the reliability of change scores
or ratings.
- Identify the basic tenets of generalizability
theory, differentiate G and D study
purposes, and combine
variance components
to calculate relative and absolute
standard errors and G-coefficients and phi-coefficients.
Use
computer software
to estimate variance components.
- Describe and apply
procedures used to determine the reliability of criterion-referenced
tests.
- Describe contemporary
conceptions of validity and associated statistical
procedures for
investigating prediction, classification,
bias in selection, other issues
in decision theory, and factor analysis.
- Locate, review, and select testing
instruments that are psychometrically
suitable and
will provide useful
and legitimate
information to meet specific
needs.
- Calculate and interpret item
statistics, and revise an assessment
instrument
using a selected
response
format.
- Explain the basic
tenets of Item Response Theory.
- Describe and compare test
bias, differential item
functioning, and adverse/disparate
impact.
- Explain methods of setting
standards and cut-off
scores as an application
of validity
theory.
- Describe the reasons
for equating tests,
and distinguish
between
horizontal and vertical
equating. Apply
equipercentile and
linear equating.
- Exhibit and apply professional
and ethical sensitivity
to human aspects
of assessment
using existing
AERA, AEA, APA, and
ACPA guidelines about
fair
testing and evaluation
practices.
Multivariate
Statistical Analysis (PSYC 608)
Continuation
of PSYC 605, with emphasis on multivariate analysis, advanced
research design and implementation
of computerized statistical analysis.(Prerequisite: Psyc
605).
Students who have taken this
course should be able to:
- Calculate the statistics associated with the following
procedures: multiple regression, discriminant analysis
(DA), MANOVA, principal components analysis, and exploratory
factor analysis.
- Interpret the statistical output associated with each
procedure.
- Identify the situations under which each procedure
is applicable.
- Identify the assumptions underlying each statistical
procedure.
- Describe dummy and effect coding in multiple regression
and compare these methods with ANOVA and ANCOVA.
- Describe procedures concerning the testing
of an interaction in multiple regression.
- Explain the problems with step-wise procedures.
- Differentiate between research questions
that dictate the use of MANOVA/DA versus
multiple
univariate
tests.
- Describe multivariate follow-up procedures
for MANOVA/DA.
- Contrast principal components analysis
and exploratory factor analysis.
- Explain different
rotation methods used in principal components and
exploratory factor
analysis and
how it relates to "simple
structure".
Assessment
and Public Policy (PSYC 770)
Delineates and compares the history and role of assessment,
accountability, and quality assurance to the governance,
funding, and purposes of higher education; describes
an implementation process of assessment for educational
programs and services. (Prerequisites: Psyc 600 or equivalent)
Students who have taken this
course should be able to:
- Describe the historical, political,
and organizational origins of assessment in higher education
including 1980's
task force reports, National Governors' Association,
state legislation, federal government and accreditation
agency interventions.
- Compare and contrast performance-funding models of
higher education in Tennessee, South Carolina, Missouri,
and Virginia.
- Describe the role of the federal government in the
governance and funding of higher education.
- Describe the influence of changing student demographics
on higher education.
- Differentiate sources of revenue available for
higher education and recent trends in their
availability (e.g. federal/state,
private/public, tuition, fees, and financial
aid.)
- Describe the major state funding strategies for
higher education.
- Describe the relationship between changing
revenue sources and cost trends and their
impact on an
institution's ability
to meet demands.
- Relate
the various levels of governance in higher education
including faculty, campus-based administrators,
public
officials, and the public.
- Describe the role of public policy toward
the governance of higher education systems.
- Describe current issues, challenges,
and trends related to the practice
of assessment
and public
policy effecting
sound assessment practice.
- Define and identify differences among
inputs, outputs, outcomes, and objectives.
- Describe
the role of information in the decision-making process.
- Describe
the importance of regular environmental scanning to understand
and respond appropriately
to such influences
as the role of online instructional
delivery.
- Identify
the characteristics of a successful evaluation program.
- Write
mission statements and program objectives possessing
clarity,
focus, and comprehensiveness.
- Write
clear objectives that are (1) understandable
to people outside one's office
or discipline,
(2) specific and action-oriented,
and (3) suggest the intended
outcomes.
- Distinguish between formative
and summative evaluation.
- Devise
and implement a tenable formative
and/or summative
evaluation plan
capable of assessing
program efficacy
on an ongoing basis
and evidencing skill in selecting
an appropriate
evaluation design.
- Report statistical
results to multiple
audiences
with clarity,
catering
to the statistical
and/or theoretical
sophistication of
each audience, while
evidencing sensitivity
to policy issues
potentially at play.
- Describe
the history of assessment research
and
application,
both in the United
States and internationally;
compare and contrast US
assessment history
and usage with
that in other
cultures
and contexts.
Assessment
Methods and Instrument Design (PSYC 812)
This course
will provide a review of psychometric issues associated
with instrument and methodology design, selection,
and interpretation. Students will be introduced to the
program evaluation standards to serve as a guide for
useful, credible, and ethical evaluation of educational
programs and projects. The standards for educational
and psychological testing will be reviewed to inform
evaluation of tests, testing practices, and the effects
of test use. Given this foundation, students will review
available instruments in assessment of critical thinking,
general education, and knowledge in academic majors.
Qualitative and quantitative methodologies will be considered,
compared, and contrasted throughout the course. Development
and refinement of surveys and assessment instruments
will serve as activities for application of delineation
of goals and objectives, hierarchical research question
development, assessment purposes, test, item or task
specification, item/task development, sampling, item
pilot, review, maintenance, and reporting procedures.
Consideration of multi-faceted validity and validation
issues will be stressed throughout the process. Students
will work on existent assessment instrument development
and refinement. Development of working relationships
with content experts will be emphasized and applied.
Students who have taken this
course should be able to:
- Read
and apply the salient professional literature to the
student's own assessment practice in
application of relevant
professional standards to practice.
- Review
available instruments in three domains (critical thinking,
general education, and assessment in a
specific major), and delineate strengths and weaknesses
for practice
in a given setting.
- Communicate
differentiation of norm- vs. criterion-referenced assessments
and their appropriate interpretations.
- Communicate
understanding and respect for philosophical differences
and value frames supporting different
assessment methodologies (i.e., qualitative and
quantitative methods).
- Apply both qualitative
and quantitative methodologies to appropriate assessment
problems.
- Communicate
understanding of differences and tensions between assessment
and accountability.
- Design
a survey research project that includes: hierarchical
research question development,
instrument development,
a plan for sampling, data collection that
supports the selected method, data codebook
development,
data analysis,
and reporting that is consistent with ethical
and best practice procedures.
- Take
an existent instrument and estimate and report the observed
reliability and
multi-faceted validity,
form appropriate
recommendations for method improvement,
and work with content experts toward
method improvement.
- Report
assessment results through identification of practical
meaning, psychometric
credibility, and limitations of the
data collected.
- Write a brief, scholarly paper linking
assessment practice with a current
validity issue.
Performance
Assessment (PSYC 814)
The optimal use of tools that assess products and processes is explored within a variety of assessment contexts. This course focuses on the design, development, and implementation of performance-based assessment. Task analysis and design, scoring schema development and use, and assessment deployment, are covered through critique and practice. Potential benefits offered by computer-based administration of performance assessments are introduced. Particular emphasis is given to validity issues throughout the course.
Students who have taken this course should be able to:
- Describe performance and portfolio assessment within the larger continuum of assessment methods
- Explain advantages and disadvantages of performance-based assessment versus other assessment methods
- Discuss “authentic” and “alternative” assessment
- Explore differences in strategies and procedures for assessing processes and products
- Design and create a complete, packaged performance assessment
- Explain the entire process of developing and implementing a performance assessment
- Conduct a task analysis
- Critique various task designs and justify suggestions for change
- Design performance tasks to measure learning objectives
- Critique and develop scoring schema for various types of performance tasks
- Explain the difference between holistic and analytical scoring systems, including benefits and limitations
- Explore the potential for performance assessment offered by computer-based administration
- Explain the benefits and limitations of portfolio assessment
- Describe situations in which various types of performance-based assessment might best be used
- Discuss reliability issues related to performance-based assessment
- Discuss validity issues related to performance-based assessment.
Classical Test Theory and Generalizability Theory (Psyc 816)
This course examines classical test theory and generalizability theory and their application to the practice of assessment. At a foundational level, model assumptions are explored and used to understand the development of different notions of reliability and dependability. At a practical level, statistical techniques developed from these two theories will be applied to develop and/or improve assessment practices.
Students who have taken this course should be able to:
- State the true score model of classical test theory its assumptions and properties
- Describe the similarities and differences between parallel, tau-equivalent, essentially tau-equivalent, and congeneric tests
- Define the reliability coefficient in classical test theory and explain its derivation from the true score model
- Describe multiple methods for estimating reliability and explain what they tell you about test scores
- Explain reliability and validity, reliability coefficients, and the validity coefficient
- Describe random and systematic error in classical test theory and generalizability theory
- Conduct an item and a reliability analysis and use the results to develop a new test or improve an existing one
- Explain and apply the unique contributions Generalizability Theory offers for performance assessment.
- Describe and explain the contribution of Generalizability Theory to understanding and expansion of classical reliability theory.
- Describe the difference between Generalizability and Decision studies and the appropriate uses of each study type to measurement development, refinement, and use for decision making.
- Differentiate between relative and absolute decisions to determine appropriate generalizability designs and coefficients.
- Demonstrate how to both differentiate among crossed, nested, random and fixed effects, and implement studies with each kind of design.
- Conduct a Generalizability Study to determine magnitude of sources of error and apply results to improve measurement designs within an applied assessment practice context (i.e., recommend facet modifications to form reliable measurement).
- Demonstrate how Generalizability Theory is used for validation study.
Structural
Equation Modeling (PSYC 830)
Exploratory
and confirmatory factor analysis, path analysis, and relevant
aspects of measurement theory are introduced.
In this context, several mathematical and technical issues
about model fitting are presented: statistical assumptions,
estimation, model evaluation, model modification, software
use, and pertinent troubleshooting strategies. (Prerequisites:
Psyc 606 and Psyc 608)
Students who have taken this
course should be able to:
- Contrast exploratory and confirmatory factor analysis.
- Compare path analysis and structural equation modeling.
- Discuss reliability and classical test theory within
a structural model framework.
- Identify and explain the two components of the general
model: Measurement and structural models.
- Describe the statistical assumptions for several
models.
- Explain estimation in general and the most
often used estimators.
- Describe structural model evaluation in general
and several of the most commonly used fit
indices.
- Explain model modification, the statistical
procedures used to inform modification,
and the issues surrounding
modification.
- Describe strategies for overcoming many
of the most common difficulties encountered
when fitting
a model
to the data.
- Demonstrate how to use SEM software
and interpret findings.
Item
Response Theory (PSYC 832)
This course will examine the use of Item Response Theory
models for test construction and ability estimation.
Models for tests with dichotomous as well as polytomous
items will be covered. Other topics for discussion include
advantages and disadvantages of IRT relative to Classical
Test Theory, the detection of differential item functioning
(or item bias), and the role of IRT in Computer Adaptive
Testing (CAT). (Prerequisite: Psyc 606)
Students who have taken this
course should be able to:
- Outline the advantages and disadvantages of IRT relative
to the Classical Test Theory.
- Describe the differences among the three popular unidimensional
IRT models in theory and application.
- Explain the concept of item and ability parameter
invariance.
- Demonstrate a general understanding of Maximum
Likelihood and Bayesian procedures as they are
applied in IRT
item and ability parameter estimation
- Identify, compare and contrast some of the various
software packages currently available for IRT
applications. Use
at least two different packages and interpret
the output.
- Describe the two basic IRT model assumptions:
unidimensionality and local independence,
and understand the implications
of these assumptions for application of IRT.
- Describe the procedures used to test the
basic assumptions of unidimensionality
and local
independence.
- Describe the concept of testlets. Explain
how testlets can be used to help meet
the assumption
of local
independence.
- Describe the various approaches to assessment
of item fit. Discuss the strengths
and weaknesses of these approaches.
Describe assessment of model-fit through
comparison of fit measures for nested
models.
- Explain the concept of person-fit.
Review and interpret research that
utilizes
item response
theory models
in providing diagnostic information,
such as identifying aberrant responses
of examinees (e.g., works by Drasgow
et
al.).
- Explain the rationale and procedures
for equating, and equate two sets
of items
(with common people
or common
items) calibrated separately.
- Apply IRT to dichotomous and polytomous
test data, and interpret the
results appropriately.
- Identify an appropriate item
response model (dichotomous,
polytomous,
or mixed) to
match measurement goals.
- Explain the concept of differential
item functioning (DIF) and
demonstrate the
ability to detect
the presence of DIF
in a test.
- Utilize item, test and information
functions to facilitate
the process of test construction.
- Describe the role of IRT
in computerized adaptive
testing
(CAT).
- Identify the considerations
for building an item
bank within the framework
of IRT in general,
and CAT in particular.
- Review and interpret
research that links
psychological processing
models for
item/task
performance
to item response
theory mathematical models
that attempt to estimate
parameters
for the cognitive
components needed
to complete task
(e.g., studies by
Embretson, Lane, and Sheen and
Mislevy).
Computers and Testing (PSYC
834)
This course focuses on the computer as a medium for the
administration and scoring of achievement tests. The strengths
and limitations of current computerized testing methods
are addressed, as well as future issues and challenges.
Topics to be discussed include linear and adaptive tests,
problem simulations, performance assessment, and expert
systems. (Prerequisite: Psyc 832)
Students who have taken this
course should be able to:
- Describe the advantages and disadvantages of computer-based
test delivery.
- Describe the various types of items that can be administered
in computer-based tests.
- Explain the differences between adaptive and nonadaptive
computer-based tests.
- Construct both adaptive and nonadaptive versions
of a computer-based achievement test.
- Describe several ways of maintaining balanced content
in a computer-based test.
- Describe different criteria for terminating a
CAT.
- Explain the arguments for and against the provision
of item review or item feedback in CATs.
- Explain the method(s) commonly used to select
items in a CAT.
- Describe different methods for scoring
computer-based tests.
- Describe several methods for controlling
the exposure of items from an item
bank when a
CAT is used.
- Explain the limitations and challenges
involved in using a computer to judge
the answer of
constructed responses.
- Distinguish the types of item selection
strategies used in norm-referenced
and criterion-referenced
CATs.
Hierarchical Linear Models (Psyc 836)
- Identify situations that prompt use of hierarchical techniques
- Explain the “unit of analysis” problem with hierarchical data and how HLM can be used to address this problem
- Understand how OLS regression and ANOVA techniques can be used with hierarchical data
- List the benefits HLM offers over OLS regression and ANOVA techniques when used with hierarchical data
- Distinguish among the following: fixed and random effects, fixed and random variables, fixed and random coefficients
- Understand maximum likelihood (ML) estimation of model parameters and differences among the various ML techniques used in HLM (e.g., FML, REML)
- Be familiar with sample size requirements in HLM
- When given a particular series of research questions, correctly specify a model or set of models to answer the research questions
- Be familiar with: a) exploratory model building processes, b) when they should be used, and c) their limitations
- List the various kinds of centering used in HLM, explain why centering is used, correctly use the various centering methods, and correctly interpret the parameters that result from the various methods of centering
- Understand: a) the assumptions of HLM, b) how to identify assumption violations, c) the impact of assumption violations on results, and d) ways to address such assumption violations
- With hierarchical data having 2- or 3-levels, including longitudinal and meta-analytic data, the student will be able to:
Use SAS and HLM software to fit various HLMs
Fit and correctly interpret models without predictors (intercept-only models) as well as models including predictors at various levels
Understand the logic behind fitting an intercept-only model to the data prior to fitting more complex models
Correctly compute and interpret the intraclass correlation coefficient (ICC)
Correctly compute and explain percent of variance accounted for at each level
Correctly interpret the model parameters and assess the fit of model to the data
Explain how residuals are computed using empirical Bayes estimation
Properly use, interpret and display residuals
Communicate analysis results effectively in writing
Be familiar with the how HLM is used with: cross-classified data, multivariate dependent variables, categorical dependent variables, and latent variables
Special Topics in Assessment (PSYC 850)
In-depth study of current topics in the field of assessment and measurement. Content will vary depending on the topic and instructor. May be repeated for different special topics. Prerequisite: Permission of instructor.
Assessment Consultation and
Practice (PSYC 855)
This course will provide guided opportunities for supervised
application of sets of assessment skills and competencies
with the development of professional self as an assessment
practitioner. Students will join with Center faculty to
engage in ongoing assessment projects concerning at-risk
students, alumni surveys, academic undergraduate and graduate
degree programs, general education, academic program reviews,
and distance education programs. Ethics will be emphasized
spanning the continua of assessment practice from establishing
consultation relationships, assessment design, data collection,
analysis, maintenance and archiving of data, report writing,
presentation of findings, toward enhanced awareness of
ethics as multifaceted: personal, corporate, political,
societal, and professional.
Students who have taken this
course should be able to:
- Describe the role
of the "Assessment Expert" in
a legal, social, and political context; delineate the
powerful role assessment processes and data have played
at an individual
as well as legal, social, and political levels; describe
the actual and potential benefits, risks, and abuses
of assessment procedures and data (e.g., the Carrie Buck
case
as one exemplar).
- Respond to relevant criticism of assessment procedures
(e.g., minority assessment, other cross-cultural
criticisms).
- Describe relevant legal and ethical issues not only
of validity and reliability, but also of fair and
appropriate
use (e.g., the 4/5 rule from the Uniform Guidelines).
- Describe how assessment practitioners/ scholars
are different from and similar to, other professionals
and/or fields
of practice and inquiry that use/develop assessment
procedures (e.g., industrial/organizational psychology,
quantitatively-oriented
psychologists, clinical psychologists, etc.)
- Compare and contrast current and historical assessment
practices and applications, and portend those
that will arise in the next 5, 10, and 20+
years.
- Describe basic concepts, models and strategies
of consultation including their underlying
principles and assumptions.
- Describe variables impacting the consultation
process at various stages of practice.
- Summarize research of past five years related
to consultation and planned change.
- Explain legal and ethical issues involved
in the practice of consultation.
- Diagnose and apply models of consultation
to specific situations.
- Apply
collaborative, problem-solving consultation with an individual
or group through each
stage of the consultation
process in an assigned situation.
- Plan
and communicate strategies needed to develop research
for
the consultation
process.
- Apply knowledge of social and
behavioral research to the
consultation process.
- Describe
the cognitive, behavioral, and affective considerations
of consulting with culturally
diverse consultees and client systems.
Doctoral Assessment Practicum
(PSYC 878)
This course will provide guided opportunities for supervised
application of sets of assessment skills and competencies
with the development of professional self as an assessment
practitioner. Students will join with Center faculty to
engage in ongoing assessment projects concerning at-risk
students, alumni surveys, academic undergraduate and graduate
degree programs, general education, academic program reviews,
and distance education programs. Ethics will be emphasized
spanning the continua of assessment practice from establishing
consultation relationships, assessment design, data collection,
analysis, maintenance and archiving of data, report writing,
and presentation of findings. Practicum is the interim
step between assistantship and internship. The student
achieves full membership as a project team member, balancing
application of the technical skills and competencies obtained
while working toward enhanced awareness of ethics as multifaceted:
personal, corporate, political, societal, and professional.
Students who have taken this
course should be able to:
- Describe and utilize quasi-experimental designs in assessment
and evaluative studies.
- Demonstrate
ability to organize and implement a project.
- Work
collaboratively as a member of a team to achieve specified
goals.
- Demonstrate
competence in assessment design.
- Seek
and create opportunities to report the findings and outcomes
of the project as a means of achieving
progress
in assessment practice.
- Exhibit and apply professional and ethical
sensitivity to human aspects of assessment
using existing
AERA, AEA, and ACPA guidelines about fair
testing and
evaluation practices.
- Interpret
assessment data to various individual and group audiences.
- Demonstrate the ability to produce and
deliver an effective oral message using
appropriate
message construction, audience
analysis, and presentation styles.
- Display effective interpersonal communication
skills in groups by defining problems,
eliciting and recognizing
member contributions, synthesizing
opinions, mediating conflicts, and reaching consensus.
- Demonstrate ability to respond to varied
communication styles and with persons
of different cultures
or groups (audience adaptability).
- Explain legal and ethical issues
involved in the practice of consultation.
- Apply collaborative, problem-solving
consultation with an individual
or group through each
stage of consultation
process in an assigned situation.
- Establish
professional consulting relationships.
Developmental Psychology
(PSYC 614 or PSYC 646)
Addressing how to design environments that facilitate
college student learning and development, this course introduces
the practical significance and application of student developmental
theories concerning both individuals and groups. An emphasis
will be placed upon alternative approaches to current student
issues and trends that are informed by student developmental
theory.
Students who have taken this
course should be able to:
- Construct an assessment method to measure a developmental
construct.
- Explain the theoretical frameworks of Perry, Chickering,
Kohlberg, Erikson, Lovinger and Belenky, Clinchy,
Goldberger, and Tarule.
- Identify the differences among student developmental,
skill, and learning outcomes.
- Identify the difference between student outcomes
and environmental operations inputs (e.g., satisfaction
or attitudinal surveys).
Describe how information collected for these
different types of assessment differ.
- Distinguish between developmental and environmental
operations.
- Construct student development
objectives and outline assessment procedures to assess
these
developmental
objectives for
a given student affairs program. Assessment
procedures include selection of methods,
procedures, and
analytical techniques.
- Outline several strategies for improving
learning beyond classroom teaching.
- Explain the role of cognitive development
learning theories in assessment method
design.
- Describe and explain at least two ways
for categorizing educational objectives.
- Relate psychological development
theory to the social, sexual, and
emotional
issues in young
adults and
describe how such issues influence
the behavior
of college students.
- Discuss the developmental differences
between the needs and issues
of the traditionally aged college
student and
nontraditional college students
(stratified by decade).
- Discuss the relations between
adolescents and parents, their
changing perceptions
of parents,
variations
in parental behavior, and family
communication.
- Discuss the force of conformity
to peer culture upon adolescents
as
well as the
rivalry between
peer and
parental influences.
- Describe the development
of identity and the variations
in identity
formation.
- Describe the development
of vocational goals and
the role
that socioeconomic,
parental,
gender, and peer influences
play.
Cognitive Psychology (PSYC
613)
Framed within the construct of a human information-processing
system, this course introduces the representation, acquisition,
retrieval and use of both declarative and procedural knowledge.
The course culminates with a few guided applications, focusing
upon the practical advantages of such a construct.
Students who have taken this
course should be able to:
- Explain the contribution of information processing and
neural network models to the theory of cognitive psychology.
- Describe methods used in cognitive psychology, including
empirical methods (e.g., latency data, verbal reports,
sorting, free recall, and eye fixation data) and
theory development methods (subtractive techniques,
information
processing techniques, and computer simulation).
- Articulate cognitive theory concerning the representation,
acquisition, and retrieval of declarative knowledge
(e.g., propositional networks, imagery, and linear
ordering),
procedural knowledge (automated basic skills, controlled
procedural knowledge and productions), and schemas,
with applications in writing, reading, and mathematics.
- Define transient memories and their relationship
to working memories and permanent memories.
- Enumerate and define three known stages of skills
acquisition.
- Describe the stages in problem solving and
reasoning as well as the difference between
domain-specific
and domain-general
problem solving.
- Indicate the role of conceptual understanding
in the transfer of knowledge and how the
transfer of automated basic skills
occurs.
- Articulate the differences between information
processing, personality, social interaction,
instructional preference,
and multidimensional approaches to the
study of learning styles.
- Describe how the different approaches
to the study of learning styles can
potentially be
used together
to provide a comprehensive
understanding of individual differences
in how students perceive, interact
with, and
respond to different
learning environments.
- Describe the prominent theoretical
models pertaining to learning style
(e.g., Kolb's
experiential
learning model,
the field-independent/dependent theory
of Witkin, Reichman-Grasha's model
of student response
styles, and the Dunn and Dunn
model).
- Explain the different approaches
to assessment of learning styles
in college
students.
Delineate the
advantages and
disadvantages of each.
- Describe the implications of individual
differences in learning style
on instructional delivery
(particularly as related to advances
in technologically delivered
instruction).
Social Psychology (PSYC 616)
Students who have taken this
course should be able to:
- Delineate the individuals, theories, and studies that
have played decisive roles in the history of social psychology.
- Describe the social psychological research methods
used to study social psychological processes such
as persuasion
and conformity, leadership and dominance, aggression
and altruism, intercultural encounters and nonverbal
behavior.
- Describe the theory and research relevant to social
cognition. Specifically, delineate the basic tenets
of theories related
to attitude formation and change and provide an
overview of attribution theory. For each theoretical
framework,
describe the relevant key research findings.
- Describe current social psychological thinking
pertaining to interpersonal relationships, emphasizing
interpersonal
attraction, friendship formation, aggression,
and prosocial behavior.
- Define and describe concepts
related to social influence (e. g., social power, persuasion,
leadership, conformity,
obedience, prejudice and discrimination). Cite
specific examples of the role of social situational
influences
on human behavior and thought.
- Describe
the concept of the self from a social psychological perspective.
Specifically,
describe how one comes
to develop a sense of self and how one's
sense of self influences
interactions with others.
- Provide specific examples of how each of
the following influence the way people
behave and
interact with
others: 1) cognitive activity, 2) individual
differences, 3) and
group phenomena.
Qualitative Research (PSYC
840)
This course is designed to give
students an introduction to the philosophical, conceptual,
and practical basis of
qualitative research. Provides an introduction to all phases
of qualitative research design: developing research questions,
doing data collection and analysis, and writing a qualitative
research proposal. (Prerequisite: Permission of instructor).
Students who have taken this
course should be able to write a qualitative research proposal
that demonstrates
their ability to:
- Identify qualitative
research questions within the given research strategy
used.
- Select
and use appropriate data collection tools given the research
strategy used.
- Sample
participants and sites.
- Manage
and store data.
- Analyze
data within a given research strategy.
- Use
qualitative data analysis software.
- Interpret
data within a given research strategy.
- Interpret
research findings within a given
research strategy.
- Determine
the quality (reliability and validity)
of data.
- Deal
with ethical issues, such as informed
consent, confidentiality
versus
anonymity, voluntary
participation,
and right to withdraw.
Psychology Foundations:
Students who have completed the
program should be able to:
- Define and describe the scope of the discipline of psychology,
the history of the field, and the diversity in what
psychologists do.
- Define and use basic psychological terminology.
- Identify major leaders in the field of psychology and
describe their work.
- Identify major psychological principles and
theories in each of the primary domains of
psychology (e.g.,
cognitive, social, developmental).
- Describe an example of the integration of
biological, social, and psychological factors
in determining
a particular form
of human behavior such as intelligence.
- Provide examples of species-specific human
behavior.
- Provide examples of individual differences
in human behavior, including:
Differences in Beliefs
Cross-Cultural Differences
Gender Differences
Genetic Differences
- Describe how psychological evidence is
acquired through the use of the scientific
method.
- Use evidence derived from application
of the scientific method to develop
informed opinions
about psychological
phenomena and behavior.
- Delineate the psychological dimensions
of health (well-being). Identify
and describe the influences
of heredity, lifestyle,
and environment on individual health.
- Recognize moral and ethical issues
as they relate to psychology.
Technology Competencies
Students who have completed the
program should be able to:
- Create a web document that contains textual, tabular,
graphical, and pictorial elements. Create relative and
absolute links.
- Compose a document (using word processing software)
that includes text, a table or graph, and an illustration
(graphic).
- Create a simple slide show and make a presentation
using the following elements: title, outline of
points, a set
of slides developing the points, and one or more
appropriate graphics incorporated into the slides.
- Create a spreadsheet by importing or entering data.
Demonstrate the use of formulas, functions, and
charts.
- Use SAS and SPSS to read, clean, manage, and
organize data. Apply a variety of appropriate
descriptive
and inferential
statistical procedures, and use the output
to write reports. Use more specialized software
as necessary
for coursework.
- Utilize
operating system commands (mainframe or PC) as necessary
to use software. Edit,
delete, copy,
move, and
rename files, use directories, invoke software
programs, and scan output for de-bugging.
- Use multiple computing environments (such
as e-mail, listservs, news readers, and
web boards)
to communicate
interactively
both locally and globally.
Use FTP to transfer a file from a PC to
another computer and from another computer
to a PC.
- Convert a file to ASCII format in order
to move it to another application or
computer.
- Classify the uses of an institutional
computer database for student information
and list
offices that might
be linked with this database.
- Discriminate among type of files: txt,
gif, jpg, doc, htm, .xls, .pdf.
- Formulate and conduct an effective
information search strategy that
includes a variety
of appropriate reference
sources,
such as library catalogs, indexes
(including PsycInfo, ERIC), bibliographies,
statistics
sources, government
publications, encyclopedias, and
resources available on the Internet.
Employ citation searching techniques,
including tracking down references
at the end of
an article or book
and using a citation index to find
sources that cite a known article.
- Identify major electronic reference
services and collections for assessment,
psychology,
and related
fields and know
where they are located.
- Search databases and web search
engines effectively and efficiently;
use
Boolean logic, limit
by date, language,
or material type, author, title,
subject, and keyword searching,
and determine
what a database
contains
and how it is organized.
- Retrieve
needed documents from a variety of locations in the
library and beyond
the walls
of the library:
locate
books, journals, newspapers,
government documents, and media in the library;
use interlibrary
loan or Document
Express to borrow books or obtain
copies of articles not owned
by the
library;
download materials
found on the Internet;
and obtain copies of reprints
directly from scholars.
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"One unique aspect of the Ph.D. program is its blending of content, skills,
and practical application."
-- Cassandra Jones,
Ph.D. student |
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