4 – 13 – 13
MSE Core – Study Guide
PSY 7190 – Advanced Cognitive Psychology
1. Understand the six components of the paradigm (the components were:
pretheoretical ideas, intellectual antecedents, analogies, concepts and language,
method, subject matter) and how they relate to things that we read (either in
support of the six components accurately describing cognitive psychology, or
ways in which the research we read contradicts the paradigm).
2. Understand the primary research methodologies that we discussed: strong
inference and the double dissociation.
3. Be able to apply important concepts in the class to other areas (e.g., educational
outcomes). Particularly relevant will be working memory, study skills
(empirically based), and the testing effect.
4. Be familiar with several of the empirical research findings from the class that
might have the potential to be applied (as in number 3). Be prepared to design
studies using the primary research methodologies (especially strong inference and
double dissociations) to evaluate potential applications of your empirical findings.
PSY 7280 – Psychological Statistics: Regression & PSY 7290 – Psychological
Statistics: ANOVA
1. First, understand the definition of sampling distribution and CLT, how sampling
distributions were developed from a population of infinity, CLT as one of many
sampling distributions depending on the statistic and sample size, sampling
distribution as a theoretical and probability distribution, and why it should be a
probability distribution to be related to inferential statistics. Then, think about
different sampling distributions in addition to the sampling distribution of sample
means (related to CLT), such as the sampling distribution of t, sampling
distribution of F, and other theoretical distributions in inferential statistics.
2. What is the definition of “degrees of freedom”? When do we need it? What is the
underlying logic of df? What is the general formula of df? Why is it important in
inferential statistics?
3. Understand the concept of R2 in general. What does it tell us in multiple
regression and in ANOVA? What is the concept of semi-partial r and semi-partial
r2? How are they different from partial r and partial r2? When we test the
significance of each X and a group of X-variables (partial F and multiple partial
F, respectively) to a given model, what role does the semi-partial r2 play?
4. GLM is a relatively new approach in data analysis. It includes almost everything
in data analysis such as multiple regression, ANOVA, chi-square test, factor
analysis, structural equation modeling, and more. First, describe how GLM
decomposes the data. Then, choose a typical between-subjects two-way ANOVA
and describe the mathematical model for it. Do the same thing for a multiple
regression case with one Y and three X variables.
5. Type I SS computes SS based on the order the variables enters the model while
Type III SS does not depend on the order. Understand the logic of each approach
and describe it in both a two-way ANOVA and a three-X-variable multiple
4 – 13 – 13
6.
7.
8.
9.
regression. Type II and Type IV SSs are both special cases of Type III SS.
Describe the relationship among them.
ANOVA is a kind of acronym of Analysis Of Variance (You can see how crazy
we are!!). For ANOVA, we are analyzing two type of variances, between-group
and within-group variance. What are the characteristics of each variance? How
were they computed? Each of the variances is estimating parameters depending
on whether Ho is true or H1 is true. If we build an F-ratio using the two variances,
we will see the nature of the F-ratio (what it is estimating). When we test a
hypothesis on the equality of population means (NOT variance), we are using the
ratio of two variances!! Explain the situation.
When we have multiple tests after or before an omnibus ANOVA, we should
control error rate (  FW ). Otherwise, our error rate will be inflated, and the test
results will be invalid. That is why several statisticians (Tukey, Scheffe, and
Bonferroni among others) developed different multiple comparison methods.
Before you talk about different methods and their strengths and weaknesses, first
explain the concept of three types of error rates and their relationship. Then, you
can describe the strengths and weaknesses of each.
Scientists try to develop and test models which may represent the reality.
Statisticians do the same thing with data. Understand that data represent reality,
and statisticians try to formulize the reality through some mathematical equations.
ANOVA and multiple regression are good examples of that endeavor.
First, describe the similarities between Between-Subjects and Within-Subjects
designs. When do we use the Between-Subjects and Within-Subjects designs?
What are the advantages and disadvantages of the Within-Subjects design over
the Between-Subjects design? What does the Within-Subjects design try to
control? Explain the strengths and weaknesses of each design with the examples
given.
SPSE 7010 – Educational Research Methodology
1. Qualitative Research: Define, describe the general characteristics of this research,
provide examples of 5 different science and math educational research contexts
where qualitative research methodologies would contribute to a deeper
understanding of the topic of the research, and explain the appropriate and
inappropriate uses of relevant qualitative research methods. Quantitative
Research: Define, describe the general characteristics of this research, provide
examples of 5 different science and math educational research contexts where
quantitative research methodologies would contribute to a deeper understanding
of the topic of the research, and explain the appropriate and inappropriate uses of
the relevant quantitative research methods.
2. Ethnographic science and math educational research: describe a math or science
educational research context (with at least two research questions) that would
suggest the use of an ethnographic educational research method. Defend the use
of ethnographic methods in this context paying specific attention to providing
substantive contribution to the literature in the domain of qualitative research on
how students learn math or science content/processes.
4 – 13 – 13
3. Research design and context—anticipate the information you need, and the
questions you would need to ask to receive that information, for the purpose of
providing contextual information essential to the effective design and
implementation of a research project to test the effectiveness of a particular set of
teaching practices or curriculum in mathematics and/or science classroom. Be
specific in your plan for an initial meeting, and develop a set of questions (10-15)
you would need to ask to get to the information you would need to set up the
research project. Additionally, compose a series of questions (6-9) to use as a
initial basis for developing research questions that would be appropriate for a
study of the teaching practices and/or curriculum materials.
4. Define triangulation as it relates to educational research. Describe the sources of
data for triangulation in a particular study. Explain the importance of triangulation
in qualitative and quantitative research studies in math and science education.
5. Human subjects research: IRB, protection of human subjects, data security, and
methodological considerations in quantitative and qualitative research plans.
Specifically, address the potential risks of “Gold Standard Research” as defined
by the Institute for Education Sciences at the U.S. Department of Education (fully
randomized controlled trials).
6. Action Research: Compare and contrast action research with narrative,
ethnographic, correlational, causal-comparative, and experimental research
methods. Provide detailed explanations for the benefits and shortcomings of
action research, as well as specific procedures to follow to insure substantive and
meaningful results from the action research project.
7. Make a comprehensive list of implicit assumptions regarding the application of
quantitative research findings, and a list of implicit assumptions regarding the
application of qualitative research findings. Provide a substantive rationale for the
appropriate use of causal-comparative research, single-subject experimental
research, narrative research, and case study research. Design and complete and
chart/table that illustrates the factors and assumptions that impact each of these
research methods.
8. Define each of the terms: reliability, validity, generalizability, credibility, and
trustworthiness. Compare and contrast the concepts and contexts when these
terms would be appropriately used. Describe the appropriate and the inappropriate
use of each of these terms, as well as the limitations associated with each of these
terms.
9. Describe the purpose and anticipated outcomes of the elements of a research plan
including, problem identification, literature review, research design, sample
selection, data collection, data analysis, data interpretation, reporting research
findings, project timeline, roles and responsibilities of the research team
members.
10. Sample size and selection: Explain the appropriate sample selection criteria and
sizes necessary for ethnographic, causal comparative, narrative, case study,
survey, correlational, experimental, and single-subject experimental research.
Defend the variation among these different research methods, suggest the
limitations on both the selection criteria and the sample size you may have
4 – 13 – 13
available, and the resultant effect on the research questions as well as they
methods that may be available to answer the questions.
SPSE 7170 – Learning Theories
Students are expected to find information from the textbook, class notes, and/or
additional related reading for the following topics.
1. Edward Thorndike - Connectionism Theory - Law of Effect; Clark Hull –
Reinforcement’s Involvement in Learning; Consequences of Behavior
2. Lev Vygotsky – Cultural/Cognitive Theory; Role of Language – Role of Culture
– Educator/Educated Relationship; Scaffolding
3. Gestalt perspective, Piaget, Bruner (Discovery Learning); Direct Instruction
(Teacher-Centered) vs. Constructivism (Learner-Centered)
4. Artificial Intelligence concept – computer simulation (Virtual Reality);
Computer and Brain – similarities/differences; Symbolic/Connectionist
Models – Implicit/Explicit Learning
5. Bandura – Social Learning Theory; Observational Learning – Imitation and
Operant Conditioning
6. Behaviorism/Theorists – Cognitivism/Theorists; Which psychological theory
or theories align(s) most closely with yours? Why?; How does learning
occur?; What does instruction look like? Learning setting? Learning
materials?; Role of learner in learning process?; What is your theory of
learning?
SPSE 7180 – Qualitative Research Methods
Topics
 Educational philosophies as related to Qualitative research and inquiry.
Examples:
o Ontology
o Epistemology
o Axiology
 The role of rhetoric and methodology in Qualitative studies and research
frameworks
 The role and importance of philosophical assumptions
 Worldviews as related to Qualitative research in terms of influence and
impact. Examples:
o Postpositivism
o Social Constructivism
o Pragmatism
 Qualitative research as a tool for advocacy
 The role and importance of social science theories in framing a Qualitative
study. Examples:
o Postmodern perspectives
o Feminist Theory
o Critical Theory and Critical Race Theory
o Queer Theory
4 – 13 – 13










o Disability Theory
Characteristics and processes involved in conducting a Qualitative study.
Know the importance and role of each characteristic.
Characteristics and framework of the five approaches to Qualitative research
design and knowledge of the depth, processes, and distinct data analyses
procedures involved in each approach. Examples:
o Narrative
o Case Study
o Phenomenology
o Ethnography
o Grounded Theory
In addition to characteristics of the five approaches, doctoral candidates
must have a working knowledge of the specific and detailed steps involved in
conducting a study reflective of each approach.
Be able to compare and contrast the five approaches
Types of approaches within the approach. Examples: Types of
phenomenology, types of grounded theory, types of case study, etc.
Differences in participant size as related to each approach
Designing overarching questions—appropriateness, openness, etc.
The role and rationale for selecting multiple data sets
The importance of Triangulation Matrix
Specific data analysis for each approach. Examples:
o Role of bracketing, horizonalization, clusters of meaning, invariant
structures
o Specific types of codes and coding process
o Generating patterns, themes, attributes and categories
o Developing grounded theory
o Analysis of culture sharing
Terms, Definitions, and Understandings
 Fieldwork
 Field texts
 Artifacts
 Storying and restorying
 Epiphanies
 Commonalities
 Lived experience
 Situational milieu
 Prolonged engagement
 Researcher-as-Instrument
 Emic and etic
 View of experiences
 “Conscious ones”
 Gatekeeper or informant
4 – 13 – 13




Holistic approach
Issues of reciprocity
Cultural portraits
Bounded system
Resources for Review and Preparation
Clandinin, D.J. & Connelly, F.M. (2004). Narrative inquiry: Experience and story in
qualitative research. San Francisco, CA: Jossey-Bass.
Creswell, J.W. (2007). Qualitative inquiry and research design: Choosing among the
five approaches (2nd ed). Thousand Oaks, CA: Sage Publications.
LeCompte, M.D. & Schensul, J.J. (1999). Designing and conducting ethnographic
research. Walnut Creek, CA: Alta Mira Press.
Lincoln, Y.S. & Guba, E.G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage
Publications.
Maykut, P. & Morehouse, R. (1994). Beginning qualitative research: A philosophical
and practical guide. Washington, DC: The Falmer Press.
Miles, M.B. & Huberman, A.M. (1994). Qualitative data analysis: An expanded
sourcebook. Thousand Oaks, CA: Sage Publications.
Moustaskas, C. (1994). Phenomenological research methods. Thousand Oaks, CA:
Sage Publications.
Yin, R.K. (2008). Case study research: Design and methods (4th ed). Thousand Oaks,
CA: Sage Publications.
SPSE 7220 – Advanced Educational Technology
All answers will need to be justified by linking related literature as
appropriate.
1. Be aware of technological trends over the last decade and be able to describe
how these trends have impacted STEM education and the students we teach
in STEM classrooms.
2. Be able to define the term “educational technology” and be able to compare
and contrast the concept of educational technology with instructional
technology by providing an example of each.
3. Digital Natives vs. Digital Immigrants: be prepared to describe a mathematics
or science education setting where, you believe, this trend (or gap) is evident.
In addition, be prepared to discuss what factors need to be considered in
addressing this issue.
4. When teaching in an online environment, be prepared to provide examples of
technological tools that support modeling, coaching, scaffolding, reflecting,
and exploring. In addition, be prepared to define Web Tools (1.0, 2.0, 3.0)
and explain examples of best practices on how to use each version in the
STEM classroom.
5. With respect to the NETS-S and the NETS-T, be prepared to explain how
these standards can be used to both better implement technology tools in
educational settings and to better prepare future STEM educators. In
4 – 13 – 13
addition, be prepared to talk about how you would use the standards in a
school setting vs. a pre-service teacher classroom. Finally, be prepared to
provide a rationale on if, you believe, the NETS have great potential to
support critical thinking in STEM classrooms.
6. Be able to describe factors than need to be considered in the planning,
implementing, and assessment phases of implementing new technologies in
school settings.
7. Be familiar with research findings from the class related to the impact of
educational technology on student achievement.
8. Understand the components of the TPACK framework. Be prepared to
discuss the literature on:
a. defining content knowledge, pedagogical knowledge and
technological knowledge
b. comparing and contrasting how each concept is related, and
c. how their relationship can inform quality technology integration in
STEM educational settings.
9. After selecting a technology tool of your choice, be prepared to show, by
using that tool, how you would supplement high-quality Science or Math
instruction (including planning, delivery, & assessment).
10. From all of the technology tools presented in the course, be prepared to
share a technology tool that you plan to use in future instruction along with a
teacher enhancement plan representing the goals, methods, and assessments
you would use to measure if the goals were met.