scientific inquiry

• Activities in Scientific Inquiry

  1. Making observations

  2. Posing questions

  3. Finding out what is already known

  4. Planning investigations

  5. Reviewing past knowledge

  6. Using tools to gather, analyze, and interpret data

  7. Proposing explanations

  8. Communicating the results
• Questionnaire Design


  One of the most critical stages in survey research process<|>A questionnaire is only as good as the questions it asks<|>Composing a good questionnaire appears easy, but it is usually the result of long, painstaking work<|>The questions must meet the basic criteria of relevance and accuracy
• Types of Questions


  • Quantitative
  • Qualitative
  • Open-ended Response Questions (Ask respondents to answer in their own words)
• Data Analysis


  An important step in answering your research question(s)<|>Analyzing data from a well-designed study helps the researcher answer questions<|>Keeping well-organized data during the collection process will help make the analysis step that much easier<|>With this data, you draw conclusions that further the research and contribute to future studies
• Good data analysis skills


  • Enable you to apply the right data to the right problems or projects, thus turning information into knowledge, recommendations & strategies
  • Gathering & collecting data is important, but if you don't have the skills to read data, the data is ultimately useless
• Turning data into meaningful information


  Lack of data isn't always a problem in organizations, it's the opposite: there's often too much information available to make a clear decision<|>You need to know it is the right data for answering your question<|>You need to draw accurate conclusions from that data<|>You need data that informs your decision-making process
• Steps in Data Analysis

  1. Organize the Data

  2. Run the chosen Statistical Tests (choose the one that is appropriate to your research: Excel, SPSS, etc)

  3. Analyze the Data (turn your data into suitable results based on ROs/RQs & Hypotheses)
• Common Data Analysis Tools

  • Excel
  • SPSS
  • PowerBI
• Basic Data Analysis Types and Applications

  • To describe (Descriptive Statistics): Frequencies, Percentages, Mean score (Average), Standard Deviation (SD) - Dispersion
  • To test relationships: Scatter plot, Correlation Analysis, Regression Analysis
  • To do comparison (Comparative Analysis): Comparative analysis based on mean scores/frequencies/percentages/Crosstab, Two-Sample T-test (compare 2 groups/variables), Analysis of Variance ANOVA (Compare more than 2 groups/variables)
  • To evaluate trend (Trend Analysis): Trend analysis based trend in mean scores/frequencies/percentages/Scatter Plot
• Conclusions must always be backed up by data
• If the data support the hypothesis, then the hypothesis is considered supported
• If the data do not support the hypothesis, then the hypothesis is considered as negated or NOT supported
• If a hypothesis is not supported, it is not a bad result! Scientists learn something from both supported or negated hypotheses
• This gives scientists an opportunity to re-look at the initial observation in a new way
• They may start over with a new hypothesis and conduct a new experiment or data collection
• Doing so is simply the process of scientific learning
• Communication


  Every research yields new findings and conclusions<|>By documenting both the successes and failures of scientific inquiry in journals, speeches, or other public documents, scientists are contributing information that will serve as a basis for future research<|>Communication is a very important component of scientific progress!
• Steps in Writing it Right

  1. Identifying important factors (Focus the findings on the important variables and topics)

  2. Organize data outputs (Arrange ideas in a logical order and in order of relevance or importance)

  3. Wordings (Keep the language as simple as the subject permits, Always help readers understand the information in the tables and charts by discussing it in the text)

  4. Information (Include the data sources used and any shortcomings in the data that may have affected the analysis, the analytical methods and tools used, the quality of the results)
• Graphic Aids


  Pictures or diagrams used to clarify complex points or emphasize a message, Should always be interpreted in the text
• Tables


  Most useful for presenting numerical information, especially when several pieces of information have been gathered about each item discussed
• Charts


  Translate numerical information into visual form so that relationships may be easily grasped
• Pie Charts


  • Show the composition of some total quantity at a particular time, Each angle, or "slice," is proportional to its percentage of the whole
• Hypothesis


  A formal statement that presents the expected relationship between an independent and dependent variable
• Hypothesis


  A tentative prediction about the nature of the relationship between two or more variables
• Hypothesis


  • It is a clear statement of what is intended to be investigated
  • It should be specified before research is conducted and openly stated in reporting the results
  • It allows to identify the research objectives, key abstract concepts involved, and its relationship to the problem statement and literature review
• Hypotheses are not moral or ethical questions
• Hypotheses are neither too specific nor too general
• Hypotheses are a prediction of consequences
• Hypotheses are considered valuable even if proven false
• Null Hypothesis (H0 or HN)


  A theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved
• Alternative Hypothesis (H1 or HA)


  A statement of what a hypothesis test is set up to establish
• Null Hypothesis


  • In a market test of a new product packaging, the null hypothesis might be that the new packaging is no better, on average, than the current packaging. H0: there is no difference between the two packages on average.
• Alternative Hypothesis


  • The alternative hypothesis might be that the new packaging has a different effect, on average, compared to that of the current packaging. H1: the two packages have different effects, on average.
  • The new packaging is better, on average, than the current packaging. H1: the new packaging is better than the current packaging, on average.
• Qualitative Research Approach


  • Use of Research Questions instead of objectives or hypothesis
  • Use of words like 'what' or 'how' to specify whether the study discovers, seeks to understand, explores or describes the experiences
  • Use of non-directional wording in the questions to describe rather than relate variables or compare groups
  • The questions are under continual review and reformulation, will evolve and change during the study
  • The questions are usually open-ended, without reference to the literature or theory
  • Use of a single focus
• Quantitative Research Approach

  • Use of research questions and objectives is more frequent in survey projects
  • Use of hypotheses is more frequent in experiments
  • Hypotheses represent relationship between variables
• Research methods include post-positivism, constructionism, quantitative/qualitative, experimental research, correlational research, descriptive research, qualitative study, phenomenological research, ethnographic research, and action research
• Case study design often involves a description of an individual case's condition or response to an intervention, and can focus on a group, institution, school, community, family, etc.
• Case series involves observations of several similar cases reported
• The choice of research method depends on the research objectives, such as determining the number of teachers planning to retire, the effectiveness of teaching methods, or describing the early years of residential schools