Semantic Differential Scales - Mass Media Research.pptx
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The semantic differential technique measures the meaning and attitude toward concepts or items using evaluative scales. Researchers found three main factors measured - activity, potency, and evaluation. Communication researchers adopted the evaluation dimension to measure attitudes by placing a concept at the top of 7-point bipolar adjective scales, such as pleasant/unpleasant. However, the document recommends developing unique adjective scales for each specific measurement situation rather than using standard scales.
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Attitude is the bridge between knowledge and practice. Thus assessment of attitude becomes an integral part of student evaluation.
Nursing is such a profession where nurses deal with the patients who are in need. So attitude of the nurses really matters to the quality of care they provide.
Not only helping the student nurses to develop a healthy attitude, but assessing the same is also an important role of an educator. Unless assessed, we will not know if the students have developed appropriate attitude to enhance their profession.
The assessment of attitude is essentially by observation of verbal and nonverbal behavior of the student and is likely to be very subjective. However, development of various attitude scales has reduced its subjectivity.
types- There are two attitude scales commonly used to assess the attitude of individuals:
Likert scale and semantic differential scale.
Likert scale was named after a psychologist Rensis Likert, who developed it in 1932 as a psychological concept measurement scale.
Likert scale is the most commonly used scaling technique.
It was developed to measure the attitudes, values and feelings of people.
Primarily, the original version of this scale was developed with a five-point scale (strongly agree, agree, uncertain, disagree and strongly disagree) containing a mixture of positive and negative declarative statements regarding measuring variables.
However, one can even observe the Likert scale now with four point (strongly agree, moderately agree, disagree and uncertain) to seven point (very strongly agree, strongly agree, agree, uncertain, disagree, strongly disagree and very strongly disagree) scaling categories.
Semantic differential scale measures individual's attitude toward objects, events or another individual.
Respondents describe their feelings on scales with semantic labels.
When bipolar adjectives are used at the end points of the scales, these are termed semantic differential scales.
This scale consists of a series of contrasting adjective pairs (good- bad, beneficial- harmful) listed on opposite ends of the bipolar scale.
The individual is given instruction to quickly tick on or in between the opposite adjective pairs.
Scoring is done thereafter by adding the construct on each statement (one to seven).
Scales: Semantic Differential Scale Summated Rating Scale
This document provides information about various types of scales used to measure attitudes and behaviors, including semantic differential scales, summated rating scales, anecdotal records, and critical incident technique. It defines each scale and discusses their characteristics, purposes, advantages, and disadvantages. For semantic differential scales, it describes how they measure the psychological meanings of objects using bipolar rating scales. For summated rating scales, it outlines the key characteristics of multiple items measured on a quantitative continuum. Anecdotal records are described as short, objective records of important behavioral incidents. Finally, critical incident technique involves writing descriptions of meaningful life events to facilitate reflection.
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Similarly, if measurements are consistent from one session to another, they are reliable and can be believed to some degree.
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Attitude is the bridge between knowledge and practice. Thus assessment of attitude becomes an integral part of student evaluation.
Nursing is such a profession where nurses deal with the patients who are in need. So attitude of the nurses really matters to the quality of care they provide.
Not only helping the student nurses to develop a healthy attitude, but assessing the same is also an important role of an educator. Unless assessed, we will not know if the students have developed appropriate attitude to enhance their profession.
The assessment of attitude is essentially by observation of verbal and nonverbal behavior of the student and is likely to be very subjective. However, development of various attitude scales has reduced its subjectivity.
types- There are two attitude scales commonly used to assess the attitude of individuals:
Likert scale and semantic differential scale.
Likert scale was named after a psychologist Rensis Likert, who developed it in 1932 as a psychological concept measurement scale.
Likert scale is the most commonly used scaling technique.
It was developed to measure the attitudes, values and feelings of people.
Primarily, the original version of this scale was developed with a five-point scale (strongly agree, agree, uncertain, disagree and strongly disagree) containing a mixture of positive and negative declarative statements regarding measuring variables.
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Semantic differential scale measures individual's attitude toward objects, events or another individual.
Respondents describe their feelings on scales with semantic labels.
When bipolar adjectives are used at the end points of the scales, these are termed semantic differential scales.
This scale consists of a series of contrasting adjective pairs (good- bad, beneficial- harmful) listed on opposite ends of the bipolar scale.
The individual is given instruction to quickly tick on or in between the opposite adjective pairs.
Scoring is done thereafter by adding the construct on each statement (one to seven).
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This document provides information about various types of scales used to measure attitudes and behaviors, including semantic differential scales, summated rating scales, anecdotal records, and critical incident technique. It defines each scale and discusses their characteristics, purposes, advantages, and disadvantages. For semantic differential scales, it describes how they measure the psychological meanings of objects using bipolar rating scales. For summated rating scales, it outlines the key characteristics of multiple items measured on a quantitative continuum. Anecdotal records are described as short, objective records of important behavioral incidents. Finally, critical incident technique involves writing descriptions of meaningful life events to facilitate reflection.
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At least one pilot study should be conducted for any newly developed scale to ensure its reliability and validity. To be useful, a measurement must possess these two related qualities.
A measure is reliable if it consistently gives the same answer. Reliability in measurement is the same as reliability in any other context.
For example, a reliable person is one who is dependable, stable, and consistent over time. An unreliable person is unstable and unpredictable and may act one way today and another way tomorrow.
Similarly, if measurements are consistent from one session to another, they are reliable and can be believed to some degree.
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This document provides an overview and assessment of several instruments used to measure behavioral and emotional status, including behavioral rating scales, classroom/home behavior instruments, social skills instruments, and attention deficit disorder instruments. It summarizes the purpose, technical characteristics, scores yielded, and suggested uses of various instruments such as the Achenbach System of Empirically Based Assessment, Behavior Rating Profile-2, Behavioral and Emotional Rating Scale, Attention Deficit Disorders Evaluation Scale-2, and Connors Rating Scales-Revised. In general, many of the instruments have adequate reliability and validity for screening purposes, though should not be used alone for diagnostic decisions.
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- It is difficult to achieve perfect isolation in psychology experiments since humans are complex and many variables can influence behavior and mental processes. Even subtle cues or expectations may influence participants.
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A methodological review of resilience
measurement scales
Gill Windle1*, Kate M Bennett2, Jane Noyes3
Abstract
Background: The evaluation of interventions and policies designed to promote resilience, and research to
understand the determinants and associations, require reliable and valid measures to ensure data quality. This
paper systematically reviews the psychometric rigour of resilience measurement scales developed for use in
general and clinical populations.
Methods: Eight electronic abstract databases and the internet were searched and reference lists of all identified
papers were hand searched. The focus was to identify peer reviewed journal articles where resilience was a key
focus and/or is assessed. Two authors independently extracted data and performed a quality assessment of the
scale psychometric properties.
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ratings. The conceptual and theoretical adequacy of a number of the scales was questionable.
Conclusion: We found no current ‘gold standard’ amongst 15 measures of resilience. A number of the scales are
in the early stages of development, and all require further validation work. Given increasing interest in resilience
from major international funders, key policy makers and practice, researchers are urged to report relevant validation
statistics when using the measures.
Background
International research on resilience has increased substan-
tially over the past two decades [1], following dissatisfac-
tion with ‘deficit’ models of illness and psychopathology
[2]. Resilience is now also receiving increasing interest
from policy and practice [3,4] in relation to its poten-
tial influence on health, well-being and quality of life
and how people respond to the various challenges of
the ageing process. Major international funders, such
as the Medical Research Council and the Economic
and Social Research Council in the UK [5] have identi-
fied resilience as an important factor for lifelong health
and well-being.
Resilience could be the key to explaining resistance to
risk across the lifespan and how people ‘bounce back’
and deal with various challenges presented from child-
hood to older age, such as ill-health. Evaluation of inter-
ventions and policies designed to promote resilience
require reliable and valid measures. However the com-
plexity of defining the construct of resilience has been
widely recognised [6-8] which has created considerable
challenges when developing an operational definition of
resilience.
Different approaches to measuring resilience across
studies have lead to inconsistencies relating to the nat-
ure of potential risk factors and protective processes,.
Attitude ppt(mba hons.)
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H046025258
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This document discusses evaluation practices and challenges in violence prevention. It provides examples of evaluations conducted on child sexual abuse prevention programs in Massachusetts and shaken baby syndrome prevention programs. It also discusses using evaluation to promote sustainability, dissemination, and teaching evaluation practices to social workers. Key challenges discussed include understanding stakeholder culture and complexity in real-world settings.
Attitude scale
The document discusses four main types of attitude scales: Likert scales, Thurstone scales, Guttman scales, and semantic differential scales. It provides examples of each type of scale and how they are constructed and used to measure attitudes. Likert scales use a rating system to measure agreement with statements, Thurstone scales assign values to statements ranked by judges, Guttman scales use a cumulative approach, and semantic differential scales measure evaluations along bi-polar adjective scales.
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The document discusses various concepts relevant to comparative social science research including:
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- Sources of error in measurement and response styles like leniency, central tendency, and proximity.
- Validity and reliability as important measurement properties.
- Factor analysis approaches to examine underlying constructs measured by observed variables.
- The strategy of creating functionally equivalent measures across countries for comparative analyses.
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FOCUSING YOUR RESEARCH EFFORTS Planning Your Research
FOCUSING YOUR RESEARCH
EFFORTS
Planning Your Research Project Chapter Four
What is the Research Design?
The research design is the general strategy that
provides the overall structures for the procedures
used in the research project. It is the planning
guide.
The Basic Format of the Research
Design
The question
The question converted to a research problem
A temporary hypothesis
Literature search
Data collection
Organization of the data
Analysis of the data
Interpretation of the data
The data either support or do not support the
hypothesis
Planning vs. Methodology
The general approach
to planning research is
similar across all
disciplines
The strategies used to
collect and analyze
data may be specific
to a particular
academic discipline
Research Planning Research Methodology
General Criteria for a Research Project
Universality (can be carried out by any competent
researcher)
Replication
Control (important for replication)
Measurement
The Nature and Role of Data
Data (plural) ‘data are’
Data ARE NOT absolute reality
Data are transient and ever changing
Primary Data are closest to truth
No researcher can glimpse ABSOLUTE TRUTH
Criteria for the Admissibility of Data
Any research effort should be replicable
Restrictions we identify are the criteria for the
admissibility of data
Standardize the data
Planning for Data Collection
What data are needed?
Where is the data located?
How will data be obtained?
How will data be interpreted?
Defining Measurement
Measurement is limiting the data of any
phenomenon – substantial or insubstantial – so that
those data may be interpreted and ultimately
compared to a particular qualitative or quantitative
standard
Measurement is ultimately a comparison: a think or
concept measured against a point of limitation
Types of Measurement Scales
Nominal Scales
Ordinal Scales
Interval Scales
Ratio Scales
Nominal Scales
A nominal scale limits the data
Nominal measurement is simplistic, but it does divide
data into discrete categories that can be compared
to one another.
Only a few statistical procedures are appropriate
for analyzing nominal data (a) mode, (b)
percentage, and (c) chi-square test
Ordinal Scales
Ordinal scales allow us to rank-order data
In addition to using statistics we can use with
nominal data, we can also use statistical procedures
to determine (a) the median, (b) the percentile rank,
and (c) Spearman’s rank order correlation
Interval Scales
An interval scale is characterized by two features:
(a) it has equal units of measurement, and (b) its
zero point has been established arbitrarily
Interval scales allow statistical analyses that are not
possible with nominal and ordinal data
Because an interval scale reflects equal distances ...
Development of assessment tools
Assessment tools in the affective domain have been developed to measure attitudes, interests, motivations, and self-efficacy. Self-report is the most common tool, where individuals provide accounts of their own attitudes. Rating scales use categories to elicit information about quantitative attributes, such as Likert scales from 1-10. Semantic differential scales assess reactions to words or concepts using bipolar adjective scales to determine directionality and intensity of reactions. These tools have been validated in studies of attitude formation, organizations, jobs, and minorities.
2015_Discrete choice experiments versus rating scale exercises to evaluate th...
This document summarizes a study that compared discrete-choice experiments (DCE) and rating scale exercises (RSE) to evaluate the importance of attributes. 254 undergraduate students completed both a DCE and RSE regarding attributes of a health-related case study. The DCE found that only 4 attributes were statistically significant, while the RSE rated all but one attribute as at least a 4 out of importance. The study found that DCE had a differentiating effect on attribute importance compared to RSE, and that determining importance from DCE requires caution, as lack of significance does not mean an attribute is not important.
300 words agree or disagree to each question Q1There are .docx
300 words agree or disagree to each question
Q1
There are various types of methods when conducting research that we’ve learned thus far in the course. There is quantitative, which consists of numerical summations and facts for summary purposes and “emphasize data that cannot be disputed because it can be objectively measured” (APUS, 2016, 1). Then there is the qualitative method, which is contrary to quantitative methods. Qualitative observations are unstructured and broad, focusing on anything the researcher deems credible to a study (Ellis, et all, 2009). Finally, there is the mixed method, which is a combination of both quantitative and qualitative methods.
There are many different types of data collections instruments that researchers use for their studies. There are: self-defined instruments, qualitative instruments, published instruments and modified instruments. Self-Defined instruments require extensive knowledge of the subject being study, including developing the steps and testing (possibly multiple) to ensure the validity of results (APUS, 2016, 2). This type of instrument is not recommended for first-time researchers. Qualitative instruments can include interview questions because the researcher has based their questions on others. Results are typically shared with experts to determine the validity of the results as well as making recommendations for change. Published instruments are data collection instruments developed by others, however these should be used cautiously because just because an instrument has been published, doesn’t necessarily equate to it being reliable. (APUS, 2016, 2). Modified instruments are simply published instruments where modifications have been made. To ensure these instruments are efficient, it is vital to ensure their validity and reliability. There are two types of validity: construct and content. Construct validity consist of whether the items align with concepts or constructs (APUS, 2016, 2). Content validity is the extent to which an instrument measures what it is intended to measure.
For my research proposal: Terrorism in Prison: Addressing Islamic Radicalism and Combating Recruitment, I utilized a mixed approach. Using both qualitative and quantitative methods were necessary due to the difficulty when utilizing a quantitative method of determining radicalism in a prison setting. I intend to use two instruments for my research: ERG22+ (Extremism Risk Guidelines) as well as interviewing and surveying convicted terrorists. The ERG22+ was the first risk assessment tool for violent extremism (Heide, et. all, 2019). It was created in the U.K. and the structure is based on 22 factors organized into three different domains: Engagement, Intent, and Capability. The ERG22+ is based on a Structured Professional Judgment (SPJ) that consists of empirical knowledge of extremists and terrorists (Powis et. all, 2019). The participants of this tool are convicted terrorists in the U.K. Next, the ERG22+ was.
An Improved sentiment classification for objective word.
Sentiment classification is an ongoing field and interesting area of research because of its application in various fields. Customer sentiments play a very important role in daily life. Currently, Sentiment classification focused on subjective statements and ignores objective statements which also carry sentiment. During the sentiment classification, problem is faced due to the ambiguous sense (meaning) of words and negation words. In word sense disambiguation method semantic scores calculated from SentiWordNet of WordNet glosses terms. The correct sense of the word is extracted and determined similarity in WordNet glosses terms. SentiWordNet extract first sense of word which used in general sense. This work aims at improving the sentiment classification by modifying the sentiment values returned by SentiWordNet and compare classification accuracy of support vector machine and naïve bays.
Qualitative Research.pptx
The document discusses several key differences between qualitative and quantitative research approaches. Qualitative research focuses on interpretation and understanding phenomena through the researcher's active involvement, while quantitative research aims for objectivity by controlling variables. Some key differences covered include the researcher's role, research design flexibility, measurement tools, and theory building processes. The document also addresses reliability, validity, and trustworthiness in qualitative research.
Stratified Sampling Technique - Probability Sampling - Mass Media Research.pptx
A stratified sample is the approach used to get adequate representation of a subsample. The characteristics of the subsample (strata or segment) may include almost any variable: age, gender, religion, income level, or even individuals who listen to specific radio stations or read certain magazines.
The strata may be defined by an almost unlimited number of characteristics; however, each additional variable or characteristic makes the subsample more difficult to find and costs to find the sample increase substantially.
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Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/scoring-and-predicting-risk-preferences/
This study presents amethodology to determine risk scores of individ-uals, for a given financial risk preference survey. To this end, we use a regression-based iterative algorithm to determine the weights for survey questions in the scoring process. Next, we generate classification models to classify individuals into risk-averse and risk-seeking categories, using a subset of survey questions. We illustrate the methodology through a sample survey with 656 respondents. We find that the demographic (indirect) questions can be almost as successful as risk-related (direct) questions in predicting risk preference classes of respon-dents. Using a decision-tree based classification model, we discuss how one can generate actionable business rules based on the findings.
attitude ppt.pdf
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RESEARCH Open AccessA methodological review of resilience.docx
RESEARCH Open Access
A methodological review of resilience
measurement scales
Gill Windle1*, Kate M Bennett2, Jane Noyes3
Abstract
Background: The evaluation of interventions and policies designed to promote resilience, and research to
understand the determinants and associations, require reliable and valid measures to ensure data quality. This
paper systematically reviews the psychometric rigour of resilience measurement scales developed for use in
general and clinical populations.
Methods: Eight electronic abstract databases and the internet were searched and reference lists of all identified
papers were hand searched. The focus was to identify peer reviewed journal articles where resilience was a key
focus and/or is assessed. Two authors independently extracted data and performed a quality assessment of the
scale psychometric properties.
Results: Nineteen resilience measures were reviewed; four of these were refinements of the original measure. All
the measures had some missing information regarding the psychometric properties. Overall, the Connor-Davidson
Resilience Scale, the Resilience Scale for Adults and the Brief Resilience Scale received the best psychometric
ratings. The conceptual and theoretical adequacy of a number of the scales was questionable.
Conclusion: We found no current ‘gold standard’ amongst 15 measures of resilience. A number of the scales are
in the early stages of development, and all require further validation work. Given increasing interest in resilience
from major international funders, key policy makers and practice, researchers are urged to report relevant validation
statistics when using the measures.
Background
International research on resilience has increased substan-
tially over the past two decades [1], following dissatisfac-
tion with ‘deficit’ models of illness and psychopathology
[2]. Resilience is now also receiving increasing interest
from policy and practice [3,4] in relation to its poten-
tial influence on health, well-being and quality of life
and how people respond to the various challenges of
the ageing process. Major international funders, such
as the Medical Research Council and the Economic
and Social Research Council in the UK [5] have identi-
fied resilience as an important factor for lifelong health
and well-being.
Resilience could be the key to explaining resistance to
risk across the lifespan and how people ‘bounce back’
and deal with various challenges presented from child-
hood to older age, such as ill-health. Evaluation of inter-
ventions and policies designed to promote resilience
require reliable and valid measures. However the com-
plexity of defining the construct of resilience has been
widely recognised [6-8] which has created considerable
challenges when developing an operational definition of
resilience.
Different approaches to measuring resilience across
studies have lead to inconsistencies relating to the nat-
ure of potential risk factors and protective processes,.
Attitude ppt(mba hons.)
Attitudes are evaluative statements that indicate one's feelings toward people, objects, events, or situations either favorably or unfavorably. An attitude can be positive or negative. Positive attitudes are characterized by optimism while negative attitudes express disdain. Attitudes are formed through experiences, classical conditioning, observation of others, and more. They influence behavior and consist of affective, cognitive, and behavioral components. To change attitudes, one can provide new information, influence of peers, resolve inconsistencies, and use communication strategies. A study assessed student attitudes and found them to be generally low positive or low negative. Suggestions to improve attitudes include visualizing goals, setting expectations, dealing with problems effectively, and maintaining an optimistic outlook
H046025258
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
CORRELATIONAL-RESEARCH.pptx
This document discusses correlational research, which examines relationships between variables without manipulating them. It defines correlational research and describes its non-experimental design, purpose to test associations between variables with limited control, and high external validity. Examples of positive, negative, and no correlations are provided. Characteristics like being non-experimental and backward-looking are outlined. Common data collection methods include surveys, observations, and secondary data. Correlation and regression analyses can quantify and predict relationships between variables, though correlation does not imply causation due to directionality and third variable problems.
Scholastic achievement of higher secondary students in science stream
This study analyzed factors that predict success for higher secondary students in the science stream in India. The study assessed 400 students on cognitive measures like intelligence and creativity, personality traits, achievement motivation, and socioeconomic status. Factor analysis identified seven factors for all students, including high intelligence, achievement, and conscientiousness. High achievers specifically exhibited traits like trust, perseverance and cooperation. Comparisons between high-achieving boys and girls found boys tended to be impulsive and from lower socioeconomic backgrounds, while high-achieving girls were stable, trusting and from higher socioeconomic statuses. The study identified personality and cognitive traits that differentiated high- and low-achieving students.
DSRA
This document discusses evaluation practices and challenges in violence prevention. It provides examples of evaluations conducted on child sexual abuse prevention programs in Massachusetts and shaken baby syndrome prevention programs. It also discusses using evaluation to promote sustainability, dissemination, and teaching evaluation practices to social workers. Key challenges discussed include understanding stakeholder culture and complexity in real-world settings.
Attitude scale
The document discusses four main types of attitude scales: Likert scales, Thurstone scales, Guttman scales, and semantic differential scales. It provides examples of each type of scale and how they are constructed and used to measure attitudes. Likert scales use a rating system to measure agreement with statements, Thurstone scales assign values to statements ranked by judges, Guttman scales use a cumulative approach, and semantic differential scales measure evaluations along bi-polar adjective scales.
CMSS FIVE
The document discusses various concepts relevant to comparative social science research including:
- Equivalence across different components of research like definition, selection, data collection etc.
- Sources of error in measurement and response styles like leniency, central tendency, and proximity.
- Validity and reliability as important measurement properties.
- Factor analysis approaches to examine underlying constructs measured by observed variables.
- The strategy of creating functionally equivalent measures across countries for comparative analyses.
- The distinction between emic and etic indicators for describing attitudes and behaviors.
FOCUSING YOUR RESEARCH EFFORTS Planning Your Research
FOCUSING YOUR RESEARCH
EFFORTS
Planning Your Research Project Chapter Four
What is the Research Design?
The research design is the general strategy that
provides the overall structures for the procedures
used in the research project. It is the planning
guide.
The Basic Format of the Research
Design
The question
The question converted to a research problem
A temporary hypothesis
Literature search
Data collection
Organization of the data
Analysis of the data
Interpretation of the data
The data either support or do not support the
hypothesis
Planning vs. Methodology
The general approach
to planning research is
similar across all
disciplines
The strategies used to
collect and analyze
data may be specific
to a particular
academic discipline
Research Planning Research Methodology
General Criteria for a Research Project
Universality (can be carried out by any competent
researcher)
Replication
Control (important for replication)
Measurement
The Nature and Role of Data
Data (plural) ‘data are’
Data ARE NOT absolute reality
Data are transient and ever changing
Primary Data are closest to truth
No researcher can glimpse ABSOLUTE TRUTH
Criteria for the Admissibility of Data
Any research effort should be replicable
Restrictions we identify are the criteria for the
admissibility of data
Standardize the data
Planning for Data Collection
What data are needed?
Where is the data located?
How will data be obtained?
How will data be interpreted?
Defining Measurement
Measurement is limiting the data of any
phenomenon – substantial or insubstantial – so that
those data may be interpreted and ultimately
compared to a particular qualitative or quantitative
standard
Measurement is ultimately a comparison: a think or
concept measured against a point of limitation
Types of Measurement Scales
Nominal Scales
Ordinal Scales
Interval Scales
Ratio Scales
Nominal Scales
A nominal scale limits the data
Nominal measurement is simplistic, but it does divide
data into discrete categories that can be compared
to one another.
Only a few statistical procedures are appropriate
for analyzing nominal data (a) mode, (b)
percentage, and (c) chi-square test
Ordinal Scales
Ordinal scales allow us to rank-order data
In addition to using statistics we can use with
nominal data, we can also use statistical procedures
to determine (a) the median, (b) the percentile rank,
and (c) Spearman’s rank order correlation
Interval Scales
An interval scale is characterized by two features:
(a) it has equal units of measurement, and (b) its
zero point has been established arbitrarily
Interval scales allow statistical analyses that are not
possible with nominal and ordinal data
Because an interval scale reflects equal distances ...
Development of assessment tools
Assessment tools in the affective domain have been developed to measure attitudes, interests, motivations, and self-efficacy. Self-report is the most common tool, where individuals provide accounts of their own attitudes. Rating scales use categories to elicit information about quantitative attributes, such as Likert scales from 1-10. Semantic differential scales assess reactions to words or concepts using bipolar adjective scales to determine directionality and intensity of reactions. These tools have been validated in studies of attitude formation, organizations, jobs, and minorities.
2015_Discrete choice experiments versus rating scale exercises to evaluate th...
This document summarizes a study that compared discrete-choice experiments (DCE) and rating scale exercises (RSE) to evaluate the importance of attributes. 254 undergraduate students completed both a DCE and RSE regarding attributes of a health-related case study. The DCE found that only 4 attributes were statistically significant, while the RSE rated all but one attribute as at least a 4 out of importance. The study found that DCE had a differentiating effect on attribute importance compared to RSE, and that determining importance from DCE requires caution, as lack of significance does not mean an attribute is not important.
300 words agree or disagree to each question Q1There are .docx
300 words agree or disagree to each question
Q1
There are various types of methods when conducting research that we’ve learned thus far in the course. There is quantitative, which consists of numerical summations and facts for summary purposes and “emphasize data that cannot be disputed because it can be objectively measured” (APUS, 2016, 1). Then there is the qualitative method, which is contrary to quantitative methods. Qualitative observations are unstructured and broad, focusing on anything the researcher deems credible to a study (Ellis, et all, 2009). Finally, there is the mixed method, which is a combination of both quantitative and qualitative methods.
There are many different types of data collections instruments that researchers use for their studies. There are: self-defined instruments, qualitative instruments, published instruments and modified instruments. Self-Defined instruments require extensive knowledge of the subject being study, including developing the steps and testing (possibly multiple) to ensure the validity of results (APUS, 2016, 2). This type of instrument is not recommended for first-time researchers. Qualitative instruments can include interview questions because the researcher has based their questions on others. Results are typically shared with experts to determine the validity of the results as well as making recommendations for change. Published instruments are data collection instruments developed by others, however these should be used cautiously because just because an instrument has been published, doesn’t necessarily equate to it being reliable. (APUS, 2016, 2). Modified instruments are simply published instruments where modifications have been made. To ensure these instruments are efficient, it is vital to ensure their validity and reliability. There are two types of validity: construct and content. Construct validity consist of whether the items align with concepts or constructs (APUS, 2016, 2). Content validity is the extent to which an instrument measures what it is intended to measure.
For my research proposal: Terrorism in Prison: Addressing Islamic Radicalism and Combating Recruitment, I utilized a mixed approach. Using both qualitative and quantitative methods were necessary due to the difficulty when utilizing a quantitative method of determining radicalism in a prison setting. I intend to use two instruments for my research: ERG22+ (Extremism Risk Guidelines) as well as interviewing and surveying convicted terrorists. The ERG22+ was the first risk assessment tool for violent extremism (Heide, et. all, 2019). It was created in the U.K. and the structure is based on 22 factors organized into three different domains: Engagement, Intent, and Capability. The ERG22+ is based on a Structured Professional Judgment (SPJ) that consists of empirical knowledge of extremists and terrorists (Powis et. all, 2019). The participants of this tool are convicted terrorists in the U.K. Next, the ERG22+ was.
An Improved sentiment classification for objective word.
Sentiment classification is an ongoing field and interesting area of research because of its application in various fields. Customer sentiments play a very important role in daily life. Currently, Sentiment classification focused on subjective statements and ignores objective statements which also carry sentiment. During the sentiment classification, problem is faced due to the ambiguous sense (meaning) of words and negation words. In word sense disambiguation method semantic scores calculated from SentiWordNet of WordNet glosses terms. The correct sense of the word is extracted and determined similarity in WordNet glosses terms. SentiWordNet extract first sense of word which used in general sense. This work aims at improving the sentiment classification by modifying the sentiment values returned by SentiWordNet and compare classification accuracy of support vector machine and naïve bays.
Semelhante a Semantic Differential Scales - Mass Media Research.pptx (20)
Progress ALERT - Sim-based Assessment Tools for General Pediatric Milestones
Progress ALERT - Sim-based Assessment Tools for General Pediatric Milestones
Doing observation and Data Analysis for Qualitative Research
Doing observation and Data Analysis for Qualitative Research
RESEARCH Open AccessA methodological review of resilience.docx
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Scholastic achievement of higher secondary students in science stream
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FOCUSING YOUR RESEARCH EFFORTS Planning Your Research
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2015_Discrete choice experiments versus rating scale exercises to evaluate th...
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300 words agree or disagree to each question Q1There are .docx
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An Improved sentiment classification for objective word.
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Mais de Muhammad Awais
Qualitative Research.pptx
The document discusses several key differences between qualitative and quantitative research approaches. Qualitative research focuses on interpretation and understanding phenomena through the researcher's active involvement, while quantitative research aims for objectivity by controlling variables. Some key differences covered include the researcher's role, research design flexibility, measurement tools, and theory building processes. The document also addresses reliability, validity, and trustworthiness in qualitative research.
Stratified Sampling Technique - Probability Sampling - Mass Media Research.pptx
A stratified sample is the approach used to get adequate representation of a subsample. The characteristics of the subsample (strata or segment) may include almost any variable: age, gender, religion, income level, or even individuals who listen to specific radio stations or read certain magazines.
The strata may be defined by an almost unlimited number of characteristics; however, each additional variable or characteristic makes the subsample more difficult to find and costs to find the sample increase substantially.
Steps in Content Analysis and How to Conduct Them - Mass Media Research.pptx
In general, a content analysis is conducted in several discrete stages. Although the steps are listed here in sequence, they need not be followed in the order given.
In fact, the initial stages of analysis can easily be combined.
Nonetheless, the following steps may be used as a rough outline:
Simple Rating Scales in Mass Media Research and How to Transform Them.pptx
Rating scales are common in mass media research. Researchers frequently ask respondents to rate a list of items such as a list of programming elements that can be included in a radio station’s weekday morning show, or to rate how much respondents like radio or TV on-air personalities.
The researcher’s decision is to decide which type of scale to use: 1 to 3? 1 to 5? 1 to 7? 1 to 10? 1 to 100? Or even a 0 to 9 scale, which is commonly used by researchers who don’t have computer software to accept double-digit numbers (like 10).
Selecting a type of scale is largely a matter of personal preference, but there are a few things to consider:
Quantitative vs Qualitative - Mass Media Research.pptx
Qualitative research is a process of naturalistic inquiry that seeks in-depth understanding of social phenomena within their natural setting. It focuses on the "why" rather than the "what" of social phenomena and relies on the direct experiences of human beings as meaning-making agents in their every day lives.
Simple Random Sampling Technique - Probabiltiy Sampling - Mass Media Research...
The document discusses simple random sampling methods. It describes how simple random sampling involves giving each unit in the population an equal chance of being selected, either with or without replacement. Researchers often use random number tables to generate simple random samples by numbering units and selecting numbers from the table. For example, a researcher could sample 10 television programs out of 100 total by numbering programs 00-99 and choosing 10 random numbers. Simple random samples for surveys can also be obtained through random digit dialing or address-based dialing. The key aspects of random sampling are that each unit has an equal chance of selection and the process is free from subjective intervention.
Reliability in Content Analysis and How to Measure It - Mass Media Research.pptx
Reliability refers to levels of agreement among independent coders who code the same content using the same coding instrument. If the results fail to achieve reliability, something is amiss with the coders, the coding instructions, the category definitions, the unit of analysis, or some combination of these. To achieve acceptable levels of reliability, the following steps are recommended:
Qualitative Research Methods - How to Reliability in Qualitative Research - M...
Quantitative research uses standardized questions and instruments, while qualitative research uses flexible questioning. The key differences between quantitative and qualitative research are in the role of the researcher, research design, setting, measurement instruments, and theory building. Qualitative research ensures reliability through multiple data collection methods, an audit trail, member checks, and a research team.
Limitations of Content Analysis in Mass Media Research.pptx
Content analysis alone cannot serve as the basis for making statements about the effects of content on an audience. A study of Saturday morning cartoon programs on television might reveal that 80% of these programs contain commercials for sugared cereal, but this finding alone does not allow researchers to claim that children who watch these programs will want to purchase sugared cereals.
An additional study of the viewers is necessary
Research Error in Mass Media Research.pptx
There are two broad types of error present in all research: sampling error and non-sampling error. Sampling error occurs when the sample selected is not representative of the entire population and the results differ from what would be found in the full population. This error can be reduced by increasing the sample size. Non-sampling error includes measurement errors, data analysis mistakes, and other unpredictable influences that cannot be identified or controlled.
Likert Scale and Types of Questions - Mass Media Research.pptx
Perhaps the most commonly used scale in mass media research is the Likert scale, also called the summated rating approach.
A number of statements are developed with respect to a topic, and respondents can strongly agree, agree, be neutral, disagree, or strongly disagree with the statements.
Each response option is weighted, and each subject’s responses are added to produce a single score on the topic.
Thurstone Scales - Mass Media Research.pptx
Thurstone scales are used to measure attitudes toward concepts or constructs. They are called equal-appearing interval scales. To develop a Thurstone scale, a researcher first collects 100 or more statements related to the concept and has judges rate them on an 11-point scale of favorability. The statements are then ranked and 20-30 are chosen evenly across the ratings to construct a questionnaire. Respondents agree or disagree with the statements and their scores are the mean or median of agreed items, with disagreeing with all items scoring zero. One advantage is they provide an interval measurement scale, but developing them is time-consuming.
Difference Between EFA and CFA in Mass Media Research.pptx
Exploratory factor analysis is a statistical technique that is used to reduce data to a smaller set of summary variables and to explore the underlying theoretical structure of the phenomena. It is used to identify the structure of the relationship between the variable and the respondent.
Confirmatory factor analysis (CFA) is a multivariate statistical procedure that is used to test how well the measured variables represent the number of constructs.
Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) are similar techniques, but in exploratory factor analysis (EFA), data is simply explored and provides information about the numbers of factors required to represent the data. In exploratory factor analysis, all measured variables are related to every latent variable. But in confirmatory factor analysis (CFA), researchers can specify the number of factors required in the data and which measured variable is related to which latent variable. Confirmatory factor analysis (CFA) is a tool that is used to confirm or reject the measurement theory.
Multistage Sampling Technique - Probability Sampling - Mass Media Research.pptx
Multistage sampling is the taking of samples in stages using smaller and smaller sampling units at each stage. Multistage sampling can be a complex form of cluster sampling because it is a type of sampling which involves dividing the population into groups (or clusters).
Determining Sample Size, Sampling Error and Sample Weightage - Mass Media Res...
Determining an adequate sample size is one of the most controversial aspects of sampling. How large must a sample be to provide the desired level of confidence in the results? Unfortunately, there is no simple answer.
The size of the sample required for a study depends on at least one or more of the following seven factors: (1) project type, (2) project purpose, (3) project complexity, (4) amount of error tolerated, (5) time constraints, (6) financial constraints, and (7) previous research in the area.
However, projects intended to answer significant questions (those designed to provide information for decisions involving large sums of money or decisions that may affect people’s lives) require high levels of precision and, therefore, large samples.
Systematic Random Sampling Technique - Probability Sampling - Mass Media Rese...
Systematic sampling is a simple random sampling with a shortcut selection procedure. Everything is the same except that instead of using a list of random numbers, we first calculate a sampling interval to create a quasi-random selection method.
The sampling interval (i.e., 1 in k, where k is some number) tells us how to select elements from a sampling frame by skipping elements in the frame before selecting one for the sample.
Population vs Sample - Mass Media Research.pptx
One goal of scientific research is to describe the nature of a population—a group or class of subjects, variables, concepts, or phenomena. In some cases, an entire class or group is investigated, as in a study of prime-time television programs during the week of September 10–16. The process of examining every member in a population is called a census.
In many situations, however, an entire population cannot be examined due to time and resource constraints. Studying every member of a population is also generally cost-prohibitive and may, in fact, confound the research because measurements of large numbers of people often affect measurement quality
The usual procedure in these instances is to take a sample from the population.
How to Do Literature Review in Mass Media Research.pptx
Choose a topic. Define your research question.
Your literature review should be guided by a central research question. Remember, it is not a collection of loosely related studies in a field but instead represents background and research developments related to a specific research question, interpreted and analyzed by you in a synthesized way.
Decide on the scope of your review.
How many studies do you need to look at? How comprehensive should it be? How many years should it cover?
Types of Non Probability Sampling - Mass Media Research.pptx
The document discusses four types of non-probability sampling: convenience sampling, purposive sampling, quota sampling, and snowball sampling. Convenience sampling involves readily available subjects but lacks representation of the overall population. Purposive sampling selects subjects with specific characteristics. Quota sampling aims for a predetermined percentage of certain groups. Snowball sampling starts with a few subjects who then refer additional subjects.
Guttman Scale - Mass Media Research.pptx
Guttman scaling arranges items along a continuum based on level of extremity, so that agreeing with a less extreme item implies agreeing with all preceding items. An example 4-item scale addresses indecent TV programming, with Statement 4 being the most extreme position of banning it. A valid Guttman scale means those agreeing with later statements will also agree with preceding milder statements. Total score on the scale is determined by number of items agreed with. While difficult to develop, Guttman scales are used in political science and other fields to measure attitudes.
Mais de Muhammad Awais (20)
Stratified Sampling Technique - Probability Sampling - Mass Media Research.pptx
Stratified Sampling Technique - Probability Sampling - Mass Media Research.pptx
Steps in Content Analysis and How to Conduct Them - Mass Media Research.pptx
Steps in Content Analysis and How to Conduct Them - Mass Media Research.pptx
Simple Rating Scales in Mass Media Research and How to Transform Them.pptx
Simple Rating Scales in Mass Media Research and How to Transform Them.pptx
Quantitative vs Qualitative - Mass Media Research.pptx
Quantitative vs Qualitative - Mass Media Research.pptx
Simple Random Sampling Technique - Probabiltiy Sampling - Mass Media Research...
Simple Random Sampling Technique - Probabiltiy Sampling - Mass Media Research...
Reliability in Content Analysis and How to Measure It - Mass Media Research.pptx
Reliability in Content Analysis and How to Measure It - Mass Media Research.pptx
Qualitative Research Methods - How to Reliability in Qualitative Research - M...
Qualitative Research Methods - How to Reliability in Qualitative Research - M...
Limitations of Content Analysis in Mass Media Research.pptx
Limitations of Content Analysis in Mass Media Research.pptx
Likert Scale and Types of Questions - Mass Media Research.pptx
Likert Scale and Types of Questions - Mass Media Research.pptx
Difference Between EFA and CFA in Mass Media Research.pptx
Difference Between EFA and CFA in Mass Media Research.pptx
Multistage Sampling Technique - Probability Sampling - Mass Media Research.pptx
Multistage Sampling Technique - Probability Sampling - Mass Media Research.pptx
Determining Sample Size, Sampling Error and Sample Weightage - Mass Media Res...
Determining Sample Size, Sampling Error and Sample Weightage - Mass Media Res...
Systematic Random Sampling Technique - Probability Sampling - Mass Media Rese...
Systematic Random Sampling Technique - Probability Sampling - Mass Media Rese...
How to Do Literature Review in Mass Media Research.pptx
How to Do Literature Review in Mass Media Research.pptx
Types of Non Probability Sampling - Mass Media Research.pptx
Types of Non Probability Sampling - Mass Media Research.pptx
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Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
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