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JMU >> CARS >> Graduate Programs >> Ph.D. in Assessment and Measurement >> Course Descriptions and Objectives

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.

 

 

Doctoral student Cassandra Jones
"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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