It is very important topic for new researchers
It covers following points:
Ethical and legal issue in research
various ethical issues discussed
various legal issues discussed
by
Dr. Qaisar Abbas Janjua
The presentation is about Plagiarism - What it is; How to avoid it; How to find it; Citation Methods; Writing style; Methods for citing various sources. A verbal consent of Prof. Dr. C. B. Bhatt was obtained (at 4.15pm on Dt. 26-11-2016 at Hall A-2, GTU, Chandkheda) to float the presentation online in benefits of the research scholar society.
It is very important topic for new researchers
It covers following points:
Ethical and legal issue in research
various ethical issues discussed
various legal issues discussed
by
Dr. Qaisar Abbas Janjua
The presentation is about Plagiarism - What it is; How to avoid it; How to find it; Citation Methods; Writing style; Methods for citing various sources. A verbal consent of Prof. Dr. C. B. Bhatt was obtained (at 4.15pm on Dt. 26-11-2016 at Hall A-2, GTU, Chandkheda) to float the presentation online in benefits of the research scholar society.
Orthogonal Property of Standard Design/Orthogonality of Design and Factorial ...Hasnat Israq
This provides the basic description of Orthogonality of Design and Missing Values & Factorial Experiment under Design and Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists .
Basic Concepts of Experimental Design & Standard Design ( Statistics )Hasnat Israq
This gives the basic description of Design and Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists
Orthogonal Property of Standard Design/Orthogonality of Design and Factorial ...Hasnat Israq
This provides the basic description of Orthogonality of Design and Missing Values & Factorial Experiment under Design and Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists .
Basic Concepts of Experimental Design & Standard Design ( Statistics )Hasnat Israq
This gives the basic description of Design and Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists
A rigorous, online, hands-on training course designed to teach students PL/SQL concepts, constructs and features; develop in them industry best-practices, and enable participants to be fluent and fast PL/SQL developers.
Email me at dwight.cummings@yahoo.com
Workshop 6 SMART goal setting for stress reductionmarkdarransutton
Workshop 6/6. In this final workshop we explore how to set SMART goals for Stress reduction. Participants answer questions to look at the best methods or techniques for them to reduce stress, and prioritise them. SMART goals and their use is explained. Using an example participants then create their own smart goals based on their preferred method of stress reduction. Participants end the class with a full awareness of Stress, strategies and techniques for combating stress and the ability to create SMART goals.
http://www.markdsutton.com/
The student will demonstrate an understanding from differing points of view on the same historical event or issue by assessing claims from different sources, their reasoning, and evidence of such events.
A Research problem is a problem that a researcher wants to solve moreover, it is an issues or a concern that an investigator / researcher presents and justifies in a research study.
RESEARCH METHODOLOGY
- INTRODUCTION
- OBJECTIVE
- TYPES OF RESEARCH
- RESEARCH PROCESS
- RESEARCH PROBLEM
- BROAD LITERATURE SURVEY
- HYPOTHESIS FORMULATION
- RESEARCH DESIGN
- SAMPLING
- COLLECTION OF DATA
- ANALYSIS OF DATA
- HYPOTHESIS TESTING
- PREPARATION OF REPORT
- CRITERIA OF GOOD RESEARCH
- PROBLEM ENCOUNTERED BY RESEARCHER IN INDIA
- REFERENCES
CRIS LUTHER's RESEARCH METHODOLOGIES COMPILATIONcrisluther
RESEARCH METHODOLOGIES
by Cris Luther, B.S.N.,R.N.
This material is a compilation of various information on generally acceptable knowledge, concepts, principles, theories and practices in RESEARCH. It adapts contents from various publicly acknowledged publications, authors, theorists, authorities and practitioners whose works are commonly utilized in the academe and practice, and are frequently-tested competencies locally and abroad.
The works of these authors, theorists, authorities and practitioners are indispensable in learning research methodologies as they are indispensable in the completeness of this compilation.
Care has been taken to confirm accuracy of the information presented and describes generally accepted practices. However the student who prepared this material is not responsible for errors or omissions or for any consequences from application of the information in this compilation.
The primary goal of the student is to familiarize concepts in the subject RESEARCH METHODOLOGIES based on the COURSE OUTLINE provided by his Graduate School Professor DR. HELEN B. AGGABAO. It is not intended for commercial publication and resources were acquired legally.
It is his great pleasure that this compilation be reproduced for reference of other students aiming to thoroughly understand RESEARCH METHODOLOGIES.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Neuro-symbolic is not enough, we need neuro-*semantic*
Biology 199 Lecture 2 (Research Process)
1. Research, The Research
Process, Research
Methodology
LECTURE 2 (BIOLOGY 199)
MARILEN M. PARUNGAO
2. RESEARCH
viewed as a problem-solving activity
follows a logical series of steps
(research process) which makes it
different from other problem-solving
activities
3. Research Methodology
(Leedy, 1997)
the core concept underlying the research process
the methodology controls the study itself and the processes needed to
realize the study
the methodology controls and dictates the acquisition of data,
arranges them in logical relationships, sets up a means of refining the
raw data, contrives an approach so that meanings that lie below the
surface of those data become manifest, and finally issues a
conclusion or series of conclusions that lead to an expansion of
knowledge
the entire process is a unified effort as well as an appreciation of its
component parts
4. The Process of Research:
Logical Steps
THE RESEARCH PROBLEM
PROBLEM IDENTIFICATION (LOOKING FOR A TOPIC)
CHARACTERISTICS OF A GOOD RESEARCH PROBLEM
RESEARCHABILITY OF THE PROBLEM
FORMULATION OF RESEARCH OBJECTIVES
DEFINITION OF RESEARCH OBJECTIVES
CHARACTERISTICS OF RESEARCH OBJECTIVES
5. THE RESEARCH PROBLEM
THE HEART OF THE RESEARCH
PROJECT
REQUIREMENT: TO STATE THE
PROBLEM WITH UNWAVERING
CLARITY, PRECISION
WHAT IF I SIMPLY CANNOT FIND A
GOOD PROBLEM?
6. IDENTIFICATION OF THE
PROBLEM
WHERE TO FIND INTERESTING PROBLEMS...
JOURNALS, BOOKS, ABSTRACTS (LIBRARY/TRUSTED LINKS)
RECOMMENDATION SECTIONS OF THESES AND DISSERTATIONS/JOURNAL
ARTICLES
IDEAS FROM YOUR MENTOR OR PROFESSOR
IDEAS FROM SEMINARS, RESEARCH COLLOQUIA AND CONFERENCES
PERSONAL/FAMILY EXPERIENCES
RARE/INTERESTING OCCURRENCES WHICH NEEDS TO BE EXPLAINED
TOP TEN CAUSES OF MORTALITY/MORBIDITY IN YOUR LOCALITY
7. CHARACTERISTIC OF A
RESEARCH PROBLEM
SHOULD BE OF GREAT INTEREST TO YOU
USEFUL FOR THE CONCERNED PEOPLE IN A PARTICULAR FIELD
POSSESS NOVELTY
LAYS FOUNDATION FOR FURTHER RESEARCH IN THE FIELD
CAN BE COMPLETED IN THE ALLOTTED TIME DESIRED
MUST USE APPROPRIATE AND UP-TO-DATE TECHNOOLOGY
DOES NOT CARRY ETHICAL OR MORAL IMPEDIMENTS
8. A GOOD RESEARCH
PROBLEM SHOULD BE
SMART
SPECIFIC, MEASURABLE, ACHIEVABLE,
REALISTIC, TIME-BOUND
9. IS MY PROBLEM WORTHY
OF RESEARCH?
EXTERNAL FACTORS
NOVELTY AND AVOIDANCE OF
UNNECESSARY REPETITION
PRACTICAL VALUE OF THE
PROBLEM
10. IS MY PROBLEM WORTHY
OF RESEARCH?
PERSONAL FACTORS
TRAINING AND PERSONAL QUALIFICATIONS
TIME REQUIREMENTS
AVAILABILITY OF SUBJECTS AND EQUIPMENTS
SPECIALIZED WORKING CONDITIONS
HAZARDS TO BE ENCOUNTERED
RESEARCH FUNDS (COST)
11. STATING YOUR RESEARCH
PROBLEM
THE RESEARCH PROBLEM MUST
BE STATED IN A CLEAR AND
COMPLETE GRAMMATICAL
SENTENCE IN AS FEW WORDS AS
POSSIBLE!
12. WHAT’S WRONG WITH
THESE RESEARCH
BUSING OF SCHOOL CHILDREN
RETIREMENT PLANS OF ADULTS
EFFECT OF PHARMACEUTICALS ON EMBRYO
E. COLI AND WATER QUALITY
13. FORMULATION OF
RESEARCH OBJECTIVES
RESEARCH OBJECTIVES
REFLECT THE QUESTIONS WHOSE ANSWERS THE
INVESTIGATOR WANTS TO STUDY YIELD TO
CAN BE EXPRESSED EITHER IN THE FORM OF A STATEMENT OR
A QUESTION
SERVES AS THE STEERING WHEEL IN THE CONDUCT OF A
RESEARCH PROJECT
SERVES A S AGUIDE IN SPECIFYING VARIABLES TILL
INTERPRETATION OF RESULTS
14. SAMPLE OBJECTIVES
TO DEVELOP AN OPTIMIZED PROTOCOL TO DETECT
FLAVIVIRUSES IN SERUM SAMPLES USING PCR
TO DETERMINE THE EFFICACY OF ORAL ADMINISTRATION
OF PROBIOTICS IN MANAGING OBESITY
TO ESTABLISH THE RELATIONSHIP BETWEEN PLANT
HEIGHT AND FERTILIZER CONCENTRATION IN CORN
16. GENERAL VERSUS SPECIFIC
GENERAL OBJECTIVE
a generic statement which describes in broad terms
what the study wishes to accomplish
SPECIFIC OBJECTIVE
contain indicators on how to accomplish the stated
objectives and therefore, gives direction to the research
process; identifies in detail and measureable terms
the aims of the research study
17. EXAMPLE
General Objectives:
To investigate the histological effects of neem seed kernel extract on
mouse testis
Specific Objectives
To determine/identify the changes in testes histology due to neem seed
kernel extract (NSKE) exposure
To determine the relationship between neem seed kernel extract (NSKE)
and occurrence of abnormal sperm morphology
To provide a feasible physiological basis for the anti-libido property of neem
extract
18. REVIEW OF RELATED
LITERATURE
After the research problem has been identified and the objectives
formulated, a review of related literature needs to be done.
Two Important Uses:
•
To get acquainted with the existing studies related to the
research to be conducted relative to:
- who have done the work on the problem area
- what has been found
- research design utilized
- statistical analysis applied
- problem met and how were they resolved
•
To establish a rationale or a theoretical or conceptual
framework based on previous research studies done.
19. SCOPE AND LIMITATIONS
Researcher must be shrewd in narrowing the
scope of his study without becoming concerned
with a trivial problem
Assumptions, restrictions and limitation must be
explicit with respect to the coverage of the
study
Helps focus attention on valid objectives, &
helps minimize the dangers of over
generalization
20. FACTORS TO CONSIDER IN
DELIMITING THE PROBLEM
the scope of the problem
time allotted for the conduct of the study
cost and funding
cooperation/coordination needed from other institutions or
researchers
availability of research subjects
availability of equipment needed
ethical considerations
21. EXAMPLE
Impact of continuing education for health workers
The effect of continuing education activities conducted by the
Department of Health (DOH) for its staff on their performance
The effect of workshops/seminars conducted by the DOH for
its staff on their ability to manage the different programs of the
DOH in the field
To determine the effect of the Master Trainor’s Course
conducted by the DOH on the capabilities of the participants to
plan, implement, monitor, and evaluate the training programs
they conduct in the field
23. DEFINITION
A tentative explanation for certain phenomena, or
events which have occurred or will occur (Gay,
1976)
States the researcher’s expectations concerning
the relationship between two or more variables in
the research problem
Testable statement of a potential relationship
between two or more variables (McGuigan, 1978)
24. CHARACTERISTICS OF A
GOOD HYPOTHESIS
Stated in declarative form
Stated in definite terms, the relationship between
variables
Should reflect the theory or literature that it is
based on
Should be brief and to the point
Should be testable
25. TWO TYPES OF
HYPOTHESIS
“RESEARCH HYPOTHESIS AND THE NULL HYPOTHESIS”
26. THE NULL HYPOTHESIS
Ho
Never true or established but can be possibly
disproved in the course of the experimentation
No difference relationship between the variables we
want to study
May act as a starting point and as a benchmark
against which the researcher will measure the actual
outcome of the study once the researcher has
collected the data
28. EXAMPLES
Ho : Vitamin C does not inhibit chromosomal lagging
HA : Vitamin C does inhibit chromosomal lagging by 50%
compared to placebo
Ho : Cerebral artery bypass is as effective as standard
medical therapy
HA : Cerebral artery bypass is more effective than standard
medical therapy
29. TWO TYPES OF RESEARCH
HYPOTHESIS
Non-directional – reflects a difference
between groups, but the direction of the
difference (unequal) is NOT specified
Directional – reflects a difference
between groups and the difference is
specified
30. IDENTIFICATION OF
RESEARCH VARIABLES
Variable – any trait/characteristic that
manifest differences irrespective of whether
the differences are qualitative or quantitative
Qualitative – eye color, shape of teeth, sex
Quantitative – weight, height, length, light
intensity, temperature
31. TYPES OF VARIABLE
Independent – the treatment variable
variables in the course of an experiment in an effort to understand the effects of
this manipulation on some outcome (which you know as the dependent variable)
the variable which is presumed to cause, effect, influence, or stimulate the
outcome
Dependent – outcome variables in a research study
refers to the outcome or response variable
Extraneous Variable – by themselves produce changes which may be mistaken to be
the effect of the independent variable being considered
Controlled, held constant or randomized – so the effects are neutralized, cancelled
out or equated for all conditions
32. TRY THIS...
PROBLEM: the effect of carbon dioxide
loading on plant morphology
Identify the:
Independent variable
Dependent variable
Intervening/extraneous variable
33. CONSTRUCTION OF A
RESEARCH DESIGN
represents the “plan of attack” of the researcher
in answering the research objectives
in obtaining all the relevant data in relation to objectives and hypothesis
the specific areas of concern in the choice of a research design are the
following
selection and number of subjects
control and manipulation of relevant variables
establishment of criteria to evaluate outcomes
instrumentation
maximization of internal and external validity
34. FACTORS TO CONSIDER
research objectives
feasibility
ethical considerations
economy and efficiency
internal and external validity
35. INTERNAL VALIDITY
refers to extent to which investigator is able to
control the different biases affecting the study
and in the end, measures what he really intends
to measure
Did the experimental treatment really bring about
a change in the dependent variable?
Did the independent variable make a significant
difference?
36. EXTERNAL VALIDITY
refers to the extent to which the
investigator is able to generalize the
results of his study
Are the results applicable to groups
and environment outside of
experimental setting?
37. DESIGN THE TOOLS FOR
DATA COLLECTION
Experimentation
Questionnaire
Interview schedule and forms
38. DESIGN THE PLAN FOR
DATA ANALYSIS
A number of researchers think about data analysis only
after all data has been collected
Consequences:
Some very important variables in study are either not
measured at all or collected using a measurement
scale which is inconsistent with desired mode of data
analysis
Objectives are too ambitious or non-measurable,
given the nature of the data that were collected
39. THE SOLUTION...
A good practice is to construct a dummy
table
Dummy Tables – skeleton tables drawn
to help the investigator conceptualize how
the data is going to be organized and
presented after it has been collected
40. COLLECTION OF DATA
Essential phase of the research process
Researcher employs specialized tools,
instruments and procedures depending
upon the method designed for such
activity
41. DATA PROCESSING
Process the information gathered to
prepare for and facilitate analysis and
interpretation of data.
Editing of data collection forms and
coding of responses are procedures
usually done in this stage
42. DATA ANALYSIS AND
INTERPRETATION
Involves quantification, description, and
classification of data
Statistics play a major role
Researcher must be familiar with basic
statistical concepts and procedures and must
know their limitations as well as the areas
where they may be appropriately applied
43. DRAWING CONCLUSIONS
AND RECOMMENDATIONS
Researcher summarizes the discussion
on the research findings and make a
clear concluding remarks
Researcher identifies major points that
were not raised in the present study and
could lay the framework for future
undertakings
44. WRITING OF RESEARCH
REPORT
Researcher prepares report of different
activities he has undertaken together with
his findings
Report must be well-organized and
presented in proper form and style
The basic principles of technical report
writing are followed
45. REPORT OF RESEARCH
FINDINGS
Publish findings in scientific journals and
news releases
Presentation of results in scientific
meetings