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Research Projects
This section introduces my dissertation topic, two
developmental research projects, and an information chart
to help me comprehend the qualitative and quantitative differences in
the research domain. For an overview of educational research, take a
look at the concept map The
Nature of Educational Research.
Dissertation
The Effects of Analytic Scoring Rubrics, Instructional
Guidance, and Task Type (Well- or Ill-structured) on Self-efficacy and
Academic Achievement
Core research question
Will teacher credential candidates, who are identified
with high and low self-efficacy for either the well- or ill-structured
task of developing a previously untried lesson plan format and who
receive instruction for using the task's analytic scoring rubric as
a goal-setting and self-assessment instrument, increase self-efficacy
for the task and achieve a higher academic standard for the task greater
than subjects who either receive the rubric without instruction in
how to use it or who do not receive a rubric?
Rationale for study
Rubrics are an increasingly common tool for assessing
student achievement on complex or multi-part tasks (Wiggens, 1998;
Arter & McTighe, 2001), but little empirical evidence exists to
support the claims that rubrics by themselves improve student performance
for the designated task.
Tasks can be classified as either well-structured or
ill-structured depending on the degree of detail for the end-product
of the task given to the student (Feltovich, Spiro, Coulson, &
Feltovich, 1996) and the amount of support the student receives to
accomplish the task (Salomon, Globerson, & Guterman, 1989). Ill-structured
tasks have been shown to positively affect the student's skills for
analysis, synthesis, and problem-solving (Palinscar and Brown, 1984;
Scardamalia, Bereiter & Steinbach, 1984).
Self-efficacy is a key element in motivation, which
has been shown to contribute to academic success and is a trait that
can be influenced by four factors, two of which are goal-setting and
evaluation or feedback (Bandura, 1986, 1997; Schunk, 1996).
Review of the literature indicates room for a research
study on the use of rubrics as an instrument to help student's goal-setting
and SELF-evaluation for a given task. I propose that instruction on
how to use a rubric for goal-setting and self-evaluation will increase
a student's self-efficacy for that task, particularly an ill-structured
task, but also well-structured tasks.
Quantitative
The Effects of Generative Learning Strategies and
Learning Style (Field-dependent/Field-independent) on Facilitation of
Learner Achievement of Different Educational Objectives
Abstract: The purpose of the research was to assess
the effectiveness of using a generative
learning strategy, written summaries, for improving comprehension
when reading text-based instructional materials and to investigate the
possible interaction of written summaries and the learners field-dependent
or field-independent cognitive style. Sixty students from an introductory
university course were tested for field-dependence/independence, blocked
by cognitive style and then randomly assigned to three experimental
and one control groups. The instructional treatments based on the physiology
of the human heart, were designed to guide the learner to use one of
three written summary strategies, (1) among the parts of the text and
(2) between the text and prior knowledge, beliefs, and experience, and
(3) a written summary that combines both strategies. Post treatment
achievement data were collected on four criterion measures, drawing,
terminology, identification, and comprehension, regarding the parts,
interrelationships, and functions of the heart.
[Open pdf document]
Qualitative
Characteristics of Diversity Leadership Among Faculty
of Color in Educational Technology in Higher Education
Abstract: This naturalistic research inquiry emerged
from my observation that neither the research literature nor practice
of educational technology in higher education addresses particular issues
of minority and underrepresented students. These issues are well represented
in the literature of other education fields. A possible reason for this
lack of research focus on underrepresented students may be partially
explained by a limited number of diversity leaders in the field. A diversity
leader is one who has a disposition towards multiculturalism, which
may include anyone. The research interests of faculty in educational
technology are driven in part by their personal characteristics (i.e.,
interests, philosophy, experience) and in part by the accepted norms
of the field. For further analysis, refer to my paper, By
Character and Action: Towards a Leadership Diversity Model for Educational
Technology in Higher Education [pdf].
To illuminate the uncertainty of understanding of this
phenomenon, I propose this qualitative research study based on the ethnographic
methodology. This is applied research that focuses on and seeks to explain
a societal concern. The critical phenomena are the personal and professional
characteristics and behavior of faculty of color in educational technology
programs in higher education in the U.S. The broad comparison groups
include five faculty members and select people within their sphere of
influence (i.e., mentors, peers, students). The observation strategies
for uncovering the essence of the lives of diversity leaders include
interviews and document analysis.
The goal of the study is to develop a theoretical framework for identifying
diversity leadership in educational technology. This framework can then
be used for further research of the phenomena of developing or enhancing
diversity leadership within the culture of educational technology in
higher education.
[Open pdf document]
Quantitative or Qualitative! What's
the difference?
| CONCEPT |
QUANTITATIVE |
QUALITATIVE |
| Names |
Traditional research, positivist,
experimental, |
Naturalistic inquiry, ethnographic,
postpositivist |
| |
|
|
| Reliability and Validity
(Value) |
|
Lincoln and Guba (1985): |
| |
Internal validity |
Credibility |
| |
External validity |
Transferability |
| |
Reliability |
Dependability |
| |
Objectivity |
Confirmability |
| |
|
|
| How to operationalize reliability
and validity? |
Statistical methods, randomization |
Triangulation, prolonged engagement,
thick description |
| |
|
|
| Relationship
between theory/concepts and research |
Confirmational |
Emergent |
| |
|
|
| Ontology |
Positivist
– accept a common definition of reality |
Constructivist
– reality is understood from the perspective of the subject |
| Epistemology |
Objectivism |
Rationalism |
| |
| Research strategy |
Deductive |
Inductive |
| Precise hypotheses stated at
the outset |
Hypotheses that emerge as the
study develops |
| Use standardized approach so
that experiences of people are limited to certain predetermined
response categories |
Study selected issues in depth
and details |
| Preference for precise definitions
stated at the outset |
Preference for definitions in
context or as the study progresses |
| Measures the reaction of many
subjects to a limited set of questions |
Produce a wealth of detailed
data about a much smaller number of people and cases. |
| Structured |
Unstructured |
| Preference for design or statistical
control of extraneous variables |
Preference for narrative/literary
descriptions of procedures; logical analysis in controlling/accounting
for extraneous variables |
| Specific design control for
procedural bias |
Reliance on researcher to deal
with procedural bias |
| Willingness to manipulate aspects,
situations, or conditions in studying complex phenomena |
Unwillingness to tamper with
naturally occurring phenomena |
| |
| Sampling |
Large samples selected randomly;
depends on logic and power of probability to lead to confident generalization. |
Purposefully selected small
samples: chain sampling, homogenous, extreme case, criterion, |
| |
| Data collection |
- Relationship between researcher and subject
|
Researcher is detached, , inert,
observer [distant, outsider] |
Researcher is primary data collection
tool [close, insider] |
| Treatments, surveys |
Observation, field notes, document/artifact
analysis, interview, |
| Sources of data limited |
Sources of data open, broad |
| |
Hard, reliable |
Rich, deep |
| |
Generalizing |
Particularizing |
| |
| Data analysis |
Break complex phenomena into
specific parts for analysis |
Use holistic description of
complex phenomena |
| Data reduced to numbers; attention
to assessing and improving score reliability |
Preference for narrative description;
assumes that reliability of inferences is adequate |
| |
| Communication of results |
Statistical summary of results |
Narrative description of results
themes |
|