MX SIMULADOR

The main reason for mixing qualitative and quantitative approaches is: To eliminate researcher involvement. To strengthen findings by combining numbers and meanings. To replace statistical analysis. To avoid data collection.

Which of the following is not a typical characteristic of mixed methods?. Exclusive focus on numerical results. Complementarity of approaches. Integration of data. Use of both quantitative and qualitative techniques.

Which method is most aligned with qualitative research?. Structured surveys. Numerical experiments. In-depth interviews. Standardized tests.

The qualitative approach emphasizes: Numerical predictions. Statistical generalizations. Experimental control. Context, meaning, and human experiences.

A mixed methods protocol is best described as: A systematic plan for integrating qualitative and quantitative data. A list of survey items only. A statistical formula. A random order of collecting data.

In a sequential explanatory design, the researcher: Uses only secondary data. Collects both at the same time. Collects quantitative data first, then qualitative. Collects qualitative data first, then quantitative.

A mixed methods study that seeks to expand understanding by using both numbers and stories aims at: Triangulation. Complementarity. Generalization. Reliability.

The main challenge of mixed methods regarding paradigms is: Lack of data collection tools. Conflicting assumptions between qualitative and quantitative traditions. No need for ethical considerations. Only using numerical methods.

A strength of having a clear mixed methods protocol is: Avoiding context. Ensuring systematic integration of both data types. Reducing analysis. Limiting validity.

A researcher first collects survey data and then conducts interviews for deeper insights. This represents: Mixed methods research. Descriptive statistics. Pure qualitative research. Pure quantitative research.

Which technique helps merge qualitative and quantitative findings?. Elimination of outliers. Data triangulation. Thematic reduction only. Random assignment.

A common limitation of mixed method research is: It requires fewer resources. It excludes the researcher’s interpretation. It is too easy to apply. It can be time-consuming and complex.

Why is mixed method research particularly useful in education?. Because it saves time. Because it focuses only on experiments. Because it eliminates all bias. Because it allows researchers to explore both measurable and subjective aspects of learning.

What is usually the first step in a mixed methods study?. Data collection. Report writing. Conclusion development. Research question formulation.

Why is triangulation important in mixed methods research?. It allows researchers to validate findings through different data sources. It reduces sample size. It limits interpretation. It avoids complexity.

How can researchers minimize the weaknesses of mixed methods?. Through careful design and integration planning. By using only qualitative data. By ignoring limitations. By skipping pilot testing.

In a sequential explanatory design, researchers usually: Collect quantitative data first, then qualitative. Collect qualitative data first, then quantitative. Collect both datasets at the same time. Avoid integrating results.

One main strength of mixed methods is that it: Provides richer and more valid results. Reduces participant diversity. Limits generalization. Increases bias.

What type of research question is appropriate for mixed methods?. One that focuses only on variables. One that explores both measurable and experiential aspects. One that requires no data collection. One that can be answered by numbers only.

What is one key element of a mixed methods protocol?. Defining how both datasets will be integrated. Collecting only one type of data. Avoiding validity checks. Ignoring ethical considerations.

"Weighting" in mixed methods indicates: The relative priority given to qualitative vs. quantitative strands. The frequency of data collection. The length of the literature review. The number of items in a questionnaire.

The purpose of the qualitative phase in an explanatory design is to: Generate initial codes for survey development only. Explain or elaborate unexpected quantitative results. Validate random assignment. Compute effect sizes.

A study gives greater priority to qualitative findings and uses a small survey to support themes. This best reflects: Mono-method triangulation. Quantitative-only approach. Qualitative-weighted mixed methods. Quantitative-weighted mixed methods.

A design that collects both strands at the same time and integrates them is: Sequential exploratory design. Monomethod design. Sequential explanatory design. Concurrent design.

An explanatory design generally follows which sequence?. Quantitative and qualitative simultaneously. No fixed order. Qualitative → Quantitative. Quantitative → Qualitative.

In exploratory designs, the qualitative phase often helps to: Reduce the sample to one case. Estimate confidence intervals only. Select parametric tests. Develop instruments or variables for the quantitative phase.

In a triangulation model, contradictory results should be handled by: Discarding the quantitative data. Examining design quality and offering a reasoned reconciliation. Ignoring the contradiction in the report. Discarding the qualitative data.

Which integration strategy occurs at interpretation?. Randomly discarding discrepant cases. Meta-inferences combining results across strands. Merging raw datasets into one file without analysis. Building one strand’s sample from the other.

A good reason to choose an exploratory design is to: Define constructs before measuring them broadly. Avoid interviews completely. Ensure only numeric evidence is reported. Prevent instrument development.

An exploratory design generally follows which sequence?. Simultaneous strands. Alternating weekly strands without integration. Qualitative → Quantitative. Quantitative → Qualitative.

The sequential explanatory design is best summarized as: Collect/analyze qualitative first, then quantitative to test ideas. Use only one strand. Collect both strands at the same time. Collect/analyze quantitative first, then qualitative to explain results.

Confidentiality in mixed methods should be handled by: Securing identifiers and limiting access to raw data. Storing consent forms with public datasets. Sharing all raw files for open discussion in class. Reporting names to increase credibility.

Which scenario best fits “sequential explanatory”?. Only document analysis is performed. Interviews reveal themes; survey measures prevalence. Observations and tests are gathered on the same day. Survey shows an unexpected pattern; interviews probe why.

Ethical reporting in mixed methods integration should: Exclude methodological details. Present convergences, divergences, and limitations transparently. Omit unexpected findings. Report only the convergent results.

A key contribution of historic ethical guidelines (e.g., well-known international codes) is to: Eliminate researcher responsibility. Focus only on statistical accuracy. Promote faster publication. Establish principles to prevent harm and ensure voluntary participation.

An unethical practice during data collection would be: Maintaining confidentiality. Coercing participation through grades or penalties. Providing neutral study information. Allowing questions before consent.

The primary aim of ethical review is to: Protect participants’ rights and well-being. Shorten project timelines. Replace researcher judgment. Guarantee significant results.

Which statement best reflects ethical practice with minors or vulnerable groups?. Obtain assent when appropriate and consent from guardians. Use deception without debriefing. Share identities publicly to ensure transparency. Waive consent because risks are minimal.

When selecting an appropriate mixed methods design, the FIRST consideration should be: Preference for a specific statistic. Availability of software licenses. Alignment with research purpose and questions. Institutional calendar dates.

A strength of the sequential explanatory design is: Elimination of sampling. Clear follow-up to clarify statistical patterns. Shortest total study duration. Lowest integration demand.

Which protocol is best when the goal is to explore a phenomenon deeply after numerical results?. Sequential explanatory. Randomized. Convergent. Sequential exploratory.

When a researcher emphasizes equal priority to both data types, the protocol is: Embedded design. Random design. Sequential design. Convergent design.

Mixed methods are most applicable when. The study only needs quick results. Researchers lack time. Only one clear research question exists. Both numerical trends and personal experiences are important.

Which of the following best illustrates a quantitative research question?. How do students feel about teamwork?. Why do students prefer group projects?. How do teachers describe classroom challenges?. What is the average test score of students in two schools?.

The quantitative approach is mainly characterized by: Measuring variables with numbers. Open-ended narratives. Exploring personal meanings. Observing without data collection.

In a convergent design, the researcher: Applies interviews only. Collects both quantitative and qualitative data simultaneously. Uses only surveys. Ignores data integration.

Which of the following represents a challenge in applying mixed methods protocols?. Richness of data. Time and resource demands. Access to multiple paradigms. Variety of perspectives.

Using mixed methods to cross-check results from quantitative and qualitative data is called: Triangulation. Randomization. Expansion. Exploration.

One key characteristic of mixed methods is: Collecting both quantitative and qualitative data. Ignoring research context. Avoiding triangulation. Using only experimental design.

A pragmatic paradigm in mixed methods suggests that: The choice of methods depends on research questions. Only one method should be used. Qualitative methods are always superior. Quantitative methods are mandatory.

Why might a researcher use both probability and purposive sampling?. To reduce validity. To avoid mixed results. To save time. To combine representativeness and depth of understanding.

The term “integration” in mixed methods means: Using random sampling. Separating both datasets completely. Ignoring qualitative findings. Combining data from different phases to interpret results.

What is an example of mixed data collection?. Combining surveys and interviews. Only open-ended interviews. Ignoring participant feedback. Only multiple-choice tests.

How does timing affect data collection in mixed methods?. It is irrelevant to the process. It only affects qualitative data. It determines whether data are collected sequentially or concurrently. It only changes sampling.

In which situation is a mixed methods design most applicable?. When only one type of data is required. When the research problem is simple and well-defined. When the goal is to test a single hypothesis. When both numerical trends and participants’ experiences are important.

Multi-level sampling refers to: Repeating the same sample twice. Using various sampling techniques across stages or groups. Selecting participants at only one level. Randomly excluding participants.

What is the purpose of the interpretation stage in mixed methods?. To delete non-significant data. To reject qualitative information. To report results separately. To integrate findings and explain how they complement each other.

Which of the following best describes mixed method research?. It combines quantitative and qualitative approaches. It only focuses on numerical data. It rejects triangulation. It avoids the use of interviews and surveys.

A well-formulated mixed methods question should: Avoid specifying variables. Focus exclusively on one research paradigm. Separate quantitative and qualitative purposes. Indicate the need to integrate both data types.

What happens during the data collection phase?. Only interviews are conducted. Both qualitative and quantitative data are collected. Only numbers are gathered. Only one instrument is used.

In mixed methods planning, "timing" mainly refers to: When qualitative and quantitative strands are implemented (sequence). Which instrument scale is chosen. Which software is used to analyze data. How many participants each strand includes.

A triangulation design primarily aims to: Replace statistical tests with interviews. Eliminate the need for qualitative data. Corroborate results by comparing different strands. Delay interpretation until a new study.

Theorizing or transforming perspectives" in mixed methods most closely involves: Replacing one dataset with another. Prioritizing only measurement reliability. Using a theoretical lens to guide integration and interpretation. Avoiding meta-inferences.

Which option best illustrates "mixing" data?. Ignoring one dataset if results conflict. Keeping datasets completely separate without integration. Using only descriptive statistics. Connecting qualitative findings to inform quantitative sampling.

An embedded design is characterized by: Two equally prioritized strands collected concurrently. One supportive strand nested within a primary strand. Quantitative-only inquiry. Qualitative-only inquiry.

In an embedded design within a quantitative trial, qualitative data might be used to: Explain participant experiences that affect outcomes. Replace the outcome measures entirely. Avoid using control groups. Remove the need for sampling.

Which pairing matches design and timing?. Exploratory — no order. Triangulation — concurrent. Explanatory — concurrent. Embedded — always qualitative priority.

In a sequential design, timing is best described as: Both strands run at the same time. Only quantitative data are used. One strand follows the other in phases. Only qualitative data are used.

When a qualitative component is used during a primarily quantitative intervention to understand process, the design is: Exploratory. Explanatory. Triangulation. Embedded.

Transforming qualitative data into quantitative codes for integration is an example of: Member checking. Data transformation. Mono-operations bias. Randomization.

Informed consent requires that participants: Provide data anonymously without any information. Allow use of data for any future purpose without notice. Receive clear information, volunteer freely, and can withdraw. Accept participation as part of course grades automatically.

Which resource plan best supports concurrent triangulation?. Parallel teams trained to collect and analyze both strands simultaneously. Only quantitative resources are allocated. Only qualitative resources are allocated. A single researcher working serially on each strand.

Which scenario best fits “concurrent triangulation”?. Tests precede case selection for interviews. Focus groups and tests are conducted in the same period and later merged. Only one data type is collected. Focus groups precede instrument design.

A core principle of research ethics in education is: Respect for persons, beneficence, and justice. Popularity, visibility, and marketing. Speed, efficiency, and novelty. Silence, secrecy, and exclusion.

Selecting resources (“Recursos”) in mixed methods primarily means: Avoiding training for assistants. Choosing tools, personnel, time, and budget that match the design. Using only one instrument to save time. Buying the most expensive software.

A key challenge in concurrent triangulation is: Lack of any integration step. Impossible timing control. Resolving conflicting findings across strands. No need for sampling.

A sensible final check before data collection is to: Pilot instruments/protocols and verify consent materials. Collect data before ethics approval. Decide to add participants during analysis. Skip piloting to save time.

When is it acceptable to modify consent procedures?. When the researcher is in a hurry. When participants are classmates. When the sample is small. When an ethics committee approves justified alternatives with safeguards.

A practical criterion for design selection is: The cost of printing instruments. Personal dislike of interviews. Feasibility of timing, access, and expertise. Number of pages in the report.

A concurrent triangulation design typically involves. Collecting qualitative and quantitative data simultaneously and merging results. Collecting qualitative first to build a survey. Running two separate studies with no integration. Collecting quantitative first to select cases.