Research Methods and Methodologies Portal

• The presentation is a portal on research methods and methodologies
• The proponents are Samuel Sitio, Mickael Sitompul, Brain Woderson, and Ruben Sianipar

The Portal of Research Methods and Methodologies

• The portal distinguishes between main methods like quantitative and qualitative research, but also includes others from assumptions to quality analysis with project validation and verification.
• The left side is for quantitative research methodologies using experiments and large data sets to reach conclusions, the right side covers qualitative research done investigatively with interpretative approaches using smaller data sets to create theories or artifacts.
• The left side includes methods fit for quantification, while the right includes methods suited for qualification.
• As one shifts from left to right, research methods transition from quantitative to qualitative. Methods in the middle ground can move in either direction based on what suits the research or project.
• Once a decision is made, mixing quantitative and qualitative methods within the portal's layers is not allowed.

Quantitative vs Qualitative Methods

• Quantitative methods suit research that involves variable measurements and tests of theories or hypotheses where the data collected is numerical
• An example includes testing functionality or interface in computer system development
• Quantitative methods require large data amounts and use statistical analysis to test hypotheses and ensure the accuracy of research results.
• Qualitative methods focus more on understanding meaning, opinions, and behavior
• An example includes producing temporary hypotheses or theories, or developing innovations like computer systems or new products
• Typically smaller data sets that can still provide in-depth results are gathered
• Data collection continues to the point of "saturation," which is when the information gained no longer provides new insights

Philosophical Assumptions

• Philosophical assumptions serve as the starting point in research
• They influence and direct the entire research process, shaping views about validity and suitable methods
• They then become the main perspective for the project.
• Methods in the middle can move to either side based on what suits the project
• Once the decision is made, the selected approach must be used exclusively throughout the portal's layers

Positivism and Realism

• Positivism sees reality as existing independently, testable and provable objectively, without influence from the researcher's opinions or feelings
• An example includes testing if the use of math learning apps can improve student grades by using a control group
• Post-positivism acknowledges that researcher's experiences/views can influence results and is more open to interpretation/social sciences
• Realism assumes that reality exists and can be known regardless of observation, meaning that something maintains real and specific properties irrespective of consideration or observation
• An example includes a scientist measuring data on internet speeds during different weather to discover correlation between weather and network performance
• Conclusions are drawn from facts, not assumptions or opinions

Criticalism

• Criticalism sees reality as shaped by social, historical, and cultural factors and is not a given but is created and influenced by humans over time.
• An example includes researching the contrast in technology access in rural vs urban communities
• Conduct research to identify economic factors, government policies, and infrastructure that cause uneven internet acess in rural communities
• Offer solutions to lessen imbalance like subsidized internet or construction of internet infrastructure

Research Methods

• Research methods describe the procedures for completing research tasks, from initiation to execution and conclusion of projects for academic purposes

Experiments and Non-Experiments

• Experimental research studies cause-and-effect relationships between variables and modifies one while controlling the others to observe changes
• For example, discovering if learning with music enhances student concentraion is done by splitting students and comparing test results
• Non-experimental research observes situations without manipulating variables, describing, or predicting relationships but not testing cause and effect
• For example, researching the correlation between duration of social media use and student stress by collecting survey data and analyzing any connection between social media time and high stress levels

Descriptive and Analytical Methods

• Descriptive research studies and describes the characteristics of a phenomenon without looking for reasons, using quantitative or qualitative approaches like surveys, case studies, and observations
• For example, a technology firm gathering user habits in use of mobile apps for data on features and preferences without analyzing why
• Analytical research tests hypotheses by analyzing available data/findings with goals of critical evaluation and analysis
• The method is often used for decisions like product/process design.
• For example, a company improving app design by analyzing user feedback data on aspects that need improvement

Methods of Fundamental and Applied Research

• Fundamental or basic research aims to gain new understanding of the basic principles of a phenomena without direct focus on practical application for use in developing theories or new concepts
• For example, a computer scienetist is researching artificial intelligence that mimics human thought without developing a product
• Applied research solves real-world problems/answers specific questions by applying existing knowledge, often using real-world data to develop practical solutions
• For example, a technology firm might develop a fraud-detection algorithm for online transactions

Conceptual and Empirical Methods

• Conceptual research focuses on developing or interpreting concepts through theory analysis, historical research/literature review, and critical evaluation
• For example, a searcher investigating cloud security that will analyze other research to develop a new mode for systems
• Empirical research uses experience and direct observation to gain insight, collecting/analyzing data from real-world situations to test predictions/theories
• For example, a researcher attempts to find out which methods for online learning is more effective compared to in-person by measuring real student test reults

Research Approaches: Inductive, Deductive, and Abductive

• Research approaches extract conclusions and determines the truth or error of a statement
• The most common approaches are deductive and inductive
• There are also mixed "abductive" approaches

Inductive Approach

• The inductive approach builds theories from patterns and observations in collected data performed with qualitative methods for understanding phenomena from angles
• For example, a researcher analyzing e-commerce interviews to find patterns in online shopping behavior can then conclude factors affecting decision making.

Deductive Approaches

• The deductive approach tests theories by testing pre-formulated hypotheses using quantitative methods with large amounts of data, which must be measurable/operationally defined
• To test for a relationship between study time and student test scores, researchers establish "longer study leads to higher scores", then collect data from students

Abductive Approach

• The abductive approach combines inductive/deductive methods to find the explanation based on incomplete data, seeking the likeliest possibility or assumption
• For example, a network technician spots users consistently have slow internet, they suggest high traffic during business hours to solve this by collecting data

Research Strategies/Designs (Methodologies)

• Research strategies or designs are guidelines or methodologies for planning and performing research to ensure it is systematic and produces valid data

Experimental Research

• Experimental research strategy and design control factors that affect an experiment to verify or reject hypotheses and determine cause/effect
• Typically collected in large amounts and analyzed via statistics
• For example, research a study of data compression algorithms compares the algorithms to data compression on a file

Non-Experimental, Descriptive

• Ex Post Facto Research resembles experimental research, but doesn't control/manipulate variables because data was gathered before the research began.
• Seeks causal factors among data and can't provide the effect of experimental design
• For example, a researcher wants to know how sleep affects productivity with data from employees without changing sleep habits
• Surveys are descriptive research methods for assessing attitudes/characteristics of a population/relationships between variables using questionnaires or interviews
• Cross-sectional surveys collect data at one point in time
• For example, taking data from a companies customer satisfaction with an app

Longitudinal Surveys and Case Studies

• Longitudinal surveys collect data from the same population over a period including tracking teenager media habits
• Case studies conduct empirical analysis of phenomena in real-life contexts where the boundaries between the phenomenon and its context are unclear
• Data is gathered from variety of sources to be quantified to understand productivity to be weighed to productivity in its totality

Action Research

• Action research involves direct action to address practical issues while improving strategies, practices, and understanding.
• This method is cyclical, consisting of planning, action, observation, evaluation, and critical reflection.
• School principals attempting to elevate student engagement in remote classrooms can have interactive discusions among students with response evaluation

Exploratory and Grounded Strategies

• Exploratory research explores potential relationships between variables to get initial understanding without seeking answers and identifying main problems or variables with qualitative data
• A business seeking to understand why customers are declining to take surveys and interviews
• Grounded theory develops theories from systematically collected/analyzed data by collecting data from systematic anaysis of it first
• Data doesn't make the theories but emerges data by freelancers to develop theories of adaptation for a new workforce

Ethnography

• Ethnography, originating from anthropology, studies cultures and groups in social contexts which is an analytical approach
• For example, reseach analyzes startup technology to work on the culture and measure company productivity between employees

Data Collection Methods

• Data collection methods gathering research data, where methods used depend on quantitaive and qualitative research types along with source material

Types of Data Collection

• Experiments manipulate data with a goal to test relationships between variables
• For example, data measure to algorythms which can be found with data
• Questionnaire data gathered with open and closed ended questions
• For example, costumer satisfaction surveys gather data from the range of 1-5 or open questions asking for data

Case Studies and Observations

• Case studies with analysis of partcipants
• For example, there's a study that measures sucess with the system that is in the school already
• Observations study behavior with cultural ethnography
• For example, workers analyze intereaction between employees that work in a room

Interviews and Language Analysis

• Internviews test subject based on the analysis
• For example, if the business owner was hesitant with their answer to a yes/no question
• Language and text analysys to find the overall ideas
• For example, by analyzing social media commnts

Data Analysis Methods & Statistics

• Data analysis methods analyze collected material with process including checking / cleaning / transforming / modeling data to support making sense
• The most common analyses data that are for data anaysis that are general
• Statistics analyze data by summarizing and presenting information versus inferential statistics that test the significance of findings on a population
• For example, calucating overall test scores and then comparing them

Mathematics and Coding

• Computational Methods use mathematical algorithms to process equations
• For example, weather simulations use numbered systems to caluclate the weather
• Coding that is also the processing of data to extract information
• For example, data that is analyzed through workers at the company

Analytic Induction and Data Driven Approaches

• Analytic induction and grounded theory to collect information
• For example, analysis on social media accounts that can contribute to new theories
• Data of any type to find a common baseline idea for new tests
• For example, to test new hypothesis from theories

Narrative Analysis

• Narrative analysis is about testing the general idea of the overall subject
• An example is that finding different people to contribute to an explination

Quality Assurance

• Quality control is a process to meet material that have already been passed through the researchers system
• To test that results have be tested for testing by other members

Validity in Quantitative Research

• Validity ensures the right instruments for measuring
• An example, is that if you were to test intelligence, to make sure its intelligence

Test and Validity

• Reliablity checks on the accuracy
• Some examples would be surveys can create certain scores at different dates
• Replicate code to ensure it generates the right test
• An example of it is using a test in differnt locations to generate simular feedback

Data Analysis Methods: Confirmability and Validity

• The first principles of an idea should be tested ethically, but has to be followed by an agreement
• Confirmabilty by the analysis of a topic and its ideas among other researchers
• Transferabilty by the ability to implement and refer back to the material
• An example of what data in the university

Presentation of Data

• This includes contibution which comes from original theories used in data and the logic behind its testing
• The reasearcher may create the research for themselves

Analysis Methodology in BEE-AODV Research

• Bee-AODV research was of quantitative methodology
• Uses network simulation to test algorithm effectiveness
• Relieson numerical data to measure PDR, throughput, latency, and packet loss ratio
• Contains computation and measurement with simulation software

Layer 1 - Philosophical Assumptions

• Based the classified research views and observations Selected Positivism
• Focuses on research with facts
• Used to show research with accurate data from simulations

Layer 2 and 3 - Reserach Methods & Approaches

• Category: Deductive
• From the test that will compute how the algo works and compare it to a simulation and data analysis

Layer 4, 5, 6, and 7

• The sections of the work all came from other points of testing
• And they show simularites such as how the data works and that it can be accessed by others

Key Components of Tests

• The main parts of the test that have all the elements of what they should be

Chatbot Analysis

• Chat bot research that follows its components

Chatbot - Layer 1 - Philsophical Assumption

• The category selected is of that that has been tested
• With accurate tests that have been computed to give an outcome based on what is being measured

Chatbot - Layers 2 and Onward - Testing Aspects

• The reasearcher may create the research for themselves

Explore the portal of research methods and methodologies by Samuel Sitio, Mickael Sitompul, Brain Woderson, and Ruben Sianipar. It distinguishes between quantitative and qualitative research, covering assumptions, quality analysis, project validation, and verification. The portal visualizes the transition from quantitative (left) to qualitative (right) approaches.