Research Methodology

Research Scope Note: Systematic investigation, collection, and analysis of data to reach conclusions, estimate effects, or test hypotheses (Note: Use a more specific term if possible) Research Methodology Scope Note: Procedures used in making systematic observations or otherwise obtaining data, evidence, or information as part of a research project or study (Note: Do not confuse with "Research Design," which refers to the planning and organization of such procedures) Research Design Scope Note: The underlying plan or organization of a research project or study that determines its scope and approach -- also, the process of planning and organizing research activities (Note: For documents/articles dealing with research methods or experimental procedures, use "Research Methodology") Qualitative Research Scope Note: Research providing detailed narrative descriptions and explanations of phenomena investigated, with lesser emphasis given to numerical quantifications -- methods used to collect qualitative data include ethnographic practices such as observing and interviewing. True and Quasi-Experimental Designs. ERIC/AE Digest. ACCESS ERIC 1-800-LET-ERIC Experimental designs are especially useful in addressing evaluation questions about the effectiveness and impact of programs. Emphasizing the use of comparative data as context for interpreting findings, experimental designs increase our confidence that observed outcomes are the result of a given program or innovation instead of a function of extraneous variables or events. For example, experimental designs help us to answersuch questions as the following: Would adopting a new integrated reading program improve student performance? Is TQM having a positive impact on student achievement and faculty satisfaction? Is the parent involvement program influencing parents'engagement in and satisfaction with schools? How is the school's professional development program influencing teacher's collegiality and classroom practice? As one can see from the example questions above, designs specify from whominformation is to be collected and when it is to be collected. Among the different types of experimental design, there are two general categories: true experimental design: This category of design includes more than one purposively created group, common measured outcome(s), and random assignment. [Note that individual background variables such as sex and ethnicity do not satisfy this requirement since they cannot be purposively manipulated in this way.] - quasi-experimental design: This category of design is most frequently used when it is not feasible for the researcher to use random assignment. This digest describes the strengths and limitations of specific types of quasi-experimental and true experimental design. Control Groups Scope Note: Groups that match experimental groups except that they are not exposed to the experimental variables being studied -- differences arising between the groups are then attributed to these variables (Note: Use only for discussions of the identification, selection, or treatment of control groups) Experimental Groups Scope Note: Subjects who are exposed to an experimental treatment or condition, and whose subsequent performance may be attributed to that treatment or condition (Note: Use only for discussions of the identification, selection, or treatment of experimental groups) Measurement Accuracy Achievement Rating Adaptive Testing Alternative Assessment Assessment Centers (Personnel) Auditory Evaluation Audits (Verification) Benchmarking Bibliometrics Causal Models Classroom Observation Techniques Cluster Grouping Cognitive Measurement Cohort Analysis Comparative Analysis Comparative Testing Computer Assisted Testing Confidence Testing Congruence (1970 1980) Construct Validity Content Validity Control Groups Correlation Critical Incidents Method Criticism Cutting Scores Data Analysis Data Interpretation Delphi Technique Discriminant Analysis Educational Indicators Educational Testing Effect Size Equated Scores Error of Measurement Error Patterns Evaluation Evaluation Criteria Evaluation Methods Evaluation Needs Evaluation Problems Evaluation Utilization Experimental Groups Factor Analysis Factor Structure Failure Fidelity Focus Groups Goodness of Fit Grade Equivalent Scores Grade Point Average Grade Prediction Group Testing Growth Models Guessing (Tests) Hierarchical Linear Modeling Holistic Evaluation Hypothesis Testing Identification Individual Testing Informal Assessment Intelligence Quotient Interaction Process Analysis Interrater Reliability Item Analysis Item Sampling Least Squares Statistics Lesson Observation Criteria Local Norms Matched Groups Maximum Likelihood Statistics Measurement Measurement Objectives Measurement Techniques Meta Analysis Minimum Competency Testing Monte Carlo Methods Multidimensional Scaling Multiple Regression Analysis Multitrait Multimethod Techniques Multivariate Analysis National Norms Naturalistic Observation Network Analysis Norms Observation Online Surveys Outcome Measures Parent Surveys Participant Observation Path Analysis Performance Based Assessment Performance Criteria (1968 1980) Performance Specifications (1969 1980) Personality Assessment Policy Analysis Prediction Predictive Measurement Predictive Validity Predictor Variables Pretesting Psychological Testing Q Methodology Raw Scores Reliability Replication (Evaluation) Response Style (Tests) Risk Assessment Robustness (Statistics) Sample Size Sampling Scaling Scores Scoring Scoring Formulas Scoring Rubrics Selection Criteria Self Evaluation (1966 1980) Semi Structured Interviews Skill Analysis Sociometric Techniques Standard Setting (Scoring) State Norms Statistical Analysis Statistical Bias Statistical Data Statistical Significance Structural Equation Models Structured Interviews Success Sustainability Synthesis Systems Analysis Talent Identification Task Analysis Teacher Competency Testing Test Construction Test Content Test Format Test Interpretation Test Items Test Length Test Norms Test Reliability Test Results Test Selection Test Use Test Validity Testing Testing Accommodations Testing Problems Testing Programs Transcripts (Written Records) Trend Analysis True Scores Usability Validity Value Added Models Vocational Evaluation Weight (1968 1980) Weighted Scores Writing Evaluation

Creativity & Imagination

  Difference between Creativity and Imagination:

Have you ever wondered how creativity manifests itself? Do you know how the 

inventions come into existence? What is the basis for creative thinking? Creativity relies on 

imagination, the conscious representation of what is not immediately present to the senses. 

Remember your imagination is not only an artistic influence but can inspire you as a person or 

others to add development to your lifestyle, business or work ethic. While imagination is the 

process of seeing the world in new ways and finding the hidden patterns.Creativity helps in 

converting your new and imaginative ideas into reality. People who believe in imagination cross 

the boundary of “usual” and “normal” are able to think outside the box. More importantly, if 

you have ideas, but don’t act on them, you are only imaginative but not creative. 

Students of science classes usually get the idea that involve 

careful observation and analysis of data to test hypotheses. One thing that remains shrouded in 

mystery, is how scientists decide on the particular question and give anexact answer? You might 

be surprised to know that they involve in creativity and come out with logical reasoning. 

The natural world is highly complex, and really big. Interesting scientific problems (like 

curing cancer) are usually too difficult to solve directly. The art of being a scientist involves 

continually re-imagining these big problems, mentally breaking them down into smaller, 

solvable parts, and then speculating about which of these smaller parts might be key to cracking 

open the whole subject. In other words, a scientist must imagine, in advance, 

possible outcomes from different observations, and design a research study that might help to 

decide between different hypotheses

. ifferent hypotheses.