PosterFall2014.SART-Final
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This study investigated how specific, difficult goals impact attention and performance on a sustained attention task (SART) compared to vague "do your best" goals. 19 undergraduate students were assigned to either a specific goal condition or a "do your best" condition for the SART. Results showed that specific goals led to higher accuracy on target trials, indicating greater attentional focus, but did not affect performance on non-target trials or commitment to the task. The findings suggest that specific goals help maintain attention on goal-relevant stimuli during sustained attention tasks.
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Effect of Perceived Goal Difficulty, Perceived Exercise Exertion and Sub-Goal...
This study examined the effects of sub-goals on motor task performance, and the relationship between perceived goal difficulty and perceived exercise exertion. 40 college students performed sit-ups over 6 weeks with sub-goals set at 20%, 40%, and 60% improvements from their baseline over 2 week periods. 24 subjects completed the study. Results showed significant improvements in sit-up performance over time, with 61% of participants achieving their 60% improvement goal within 4 weeks. Perceived goal difficulty and perceived exercise exertion both decreased significantly over time. A positive correlation was found between perceived goal difficulty and perceived exercise exertion. The results support that setting sub-goals can improve motor task performance and that perceived goal difficulty reflects the effort required to achieve
#1 Characteristics, Strengths, Weaknesses, Kinds of.pptx
This document discusses quantitative research methods, including its characteristics, strengths, weaknesses, and different design types. It notes that quantitative research uses numerical data and statistical analysis to make generalizations about problems. It identifies some key characteristics as using standardized instruments, objective measurement scales, and statistical analysis of relationships between variables. The document also outlines strengths like reliability and validity, and weaknesses such as being time-consuming and difficult. Finally, it describes different quantitative research design types, including experimental designs like true experiments and quasi-experiments, and non-experimental descriptive designs like surveys and correlational studies.
Design
The document discusses experimental design principles for user experience research. It describes how experiments are conducted to test hypotheses and theories by manipulating independent variables and observing their effects on dependent variables. Different experimental designs are discussed, including between-subjects, within-subjects, and mixed designs. Key factors to consider in experimental design are identified, such as controlling confounding variables, minimizing carry-over effects, and appropriately selecting and assigning subjects to conditions.
Setting of research objectives Dr. Seema Jakher
This document discusses the importance and characteristics of setting clear research objectives. It defines general and specific objectives, with specific objectives being short-term and focused on systematically addressing aspects of the problem. Specific objectives should be stated in a logical sequence, be clear, specific, measurable, attainable, realistic, and time-bound. Examples of well-written specific objectives are provided. Setting objectives guides the research process and ensures the study remains focused on answering relevant questions.
AchPer Poster Updated 4:6
This study investigated which non-cognitive factors (resilience, grit, hardiness, procrastination, conscientiousness) predict academic achievement and goal pursuit persistence in undergraduate students. The researchers found that hardiness, resilience, and conscientiousness positively predicted grade point average, while procrastination negatively predicted GPA. Only hardiness positively predicted persistence in working on impossible anagram tasks over time. The study provides insight into factors that influence students' academic success and persistence in pursuing goals.
CHAPTER 2 RDL 2.pptx
This document discusses quantitative research and different types of variables used in quantitative research. It describes experimental, quasi-experimental, and non-experimental research designs. Experimental research allows controlling variables to determine causation, while quasi-experimental and non-experimental designs observe phenomena naturally. The document also defines independent, dependent, intervening, control, and confounding variables and provides examples of each.
PPT 17 TESTS.ppt
This document discusses various types of tests that can be used as data gathering tools in educational research. It describes parametric tests as standardized tests used for large populations, while non-parametric tests are designed for smaller, specific populations. The document also discusses commercially produced tests versus researcher produced tests, as well as different types of tests like aptitude tests, achievement tests, and psychological tests that measure traits like attitudes. Reliability and validity are important concepts for tests developed by researchers.
Goal orientation educational psychology
The document summarizes several research studies on achievement goal orientation:
1) The first study examined a 3x2 achievement goal model that separates task-based, self-based, and other-based goals into approach and avoidance orientations. Two studies supported this model and found differences in antecedents and consequences of the goals.
2) A second study examined the stability of achievement goal orientations over time, finding that orientations changed across tasks but performance goals had the highest stability.
3) A third study developed the Goal Orientation Towards Teaching Scale to measure teachers' learning, proving, and avoiding orientations, which correlated differently with teacher efficacy and concerns.
A Theory-Based Framework For Assessing Domainl-Specific Problem-Solving Ability
1) The document proposes a framework for assessing problem solving ability by decomposing it into its cognitive components, including domain-specific knowledge, metacognition, and motivation.
2) It identifies specific constructs within each component to measure, such as principles, concepts, procedures for domain knowledge, and planning/monitoring for metacognition.
3) Measuring these individual constructs through multiple assessments would provide more valid and useful information than assessing problem solving as a single global construct, and help pinpoint strengths and weaknesses to guide instruction.
Correlation
This ppt is made to complete from our lecture about Correlation Design in research
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Lecture 06
The document discusses key elements of research design, including:
1. It defines a research design as a plan for investigating research questions and problems.
2. Key components of a research design are identified as the problem definition, theoretical framework, hypothesis generation, research methodology, data collection and analysis, and reporting.
3. Different types of research designs are explored, including exploratory, descriptive, and hypothesis testing designs. Factors like the level of researcher interference and study settings (contrived vs. non-contrived) are also discussed.
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PosterFall2014.SART-Final
- 1. TEMPLATE DESIGN © 2008 www.PosterPresentations.com The Use of Goals in Managing Attention Resources Woosin (Jennifer) Cho, Claire E. Smith, Kelsey L. Merlo, Howard M. Weiss Georgia Institute of Technology Abstract The goals literature suggests that specific and difficult goals are able to impact performance through the allocation and intensity of attentional resources towards a focal task. While hundreds of different tasks have supported the effectiveness of specific and difficult goals, no existing research has directly tested the mediating link of attentional resources. In this study., we directly investigate the role of attention in goals using a cognitive task. Introduction Hypothesis H1 : Specific, challenging goals will result in higher attentional pull on target tasks than vague “do your best” goals H2 : Type of goal condition will not affect performance on non- target trials H3 : Type of goal condition will not affect commitment to the task Method PARTICIPANTS - 19 Georgia Tech undergraduate students - 9 assigned to specific and difficult goal condition - 10 assigned to do-your-best goal condition MATERIALS - SART: - Infrequent no-go category: vegetables (60 targets) - Nontarget go category: animals (540 nontargets) - Personal goal: reported goal compared to assigned goal setting condition - Cover story believability: reported believed purpose and hypothesis of study compared to cover story - Demographics questionnaire: Age, gender, ethnicity, major reported - Ruminative Response Scale (RSS): trait-level responses concerning depressed mood evaluated using frequency - Cognitive failures questionnaire-memory and attention lapse (CFQ-MAL): trait-level responses concerning frequency of minor cognitive failures PERFORMANCE MEASUREMENTS - Accuracy - Reaction time - Signal detection sensitivity - Bias PROCEDURES - Completed practice run of SART using male and female names as the stimuli - Received assigned condition of either a specific and difficult goal or “do your best” goal - Began true SART - Instructed to press space bar when animal word stimuli were presented - Instructed not to press space bar when vegetable word stimuli were presented - Completed questionnaires/surveys Results Conclusion - Specific and challenging goals resulted in higher attentional pull and performance level than vague, do- your-best goals on target trials. (H1 supported) - Performance level was not affected by assigned goal condition in non-target trials (H2 supported) - Commitment to the SART was not affected by the assigned goal condition. (H3 supported) - Limitations to this study include the lab-based, self- report, and student dominated nature of the experimental design. Future application References Contact information - The relationship between goal phrasing and performance level on sustained attention tasks could be used to further understand performance on a variety of tasks. - This study is currently being integrated with a Cyberball ostracism task to examine the attentional pull of ostracism and the ability of specific and difficult goals to redirect attention to the task at hand. Locke, E. A., & Latham, G. P. (1990). A Theory of Goal Setting and Task Performance. Englewood Cliffs, NJ: Prentice-Hall, Inc. Robertson, I. H., Manly, T., Andrade, J., Baddeley, B. T., & Yiend, J. (1997). 'Oops!': Performance correlates of everday attentional failures in traumatic brain injured and normal subjects. Neuropsychologia, 35(6), 747-758. Woosin (Jennifer) Cho, Claire E. Smith, Kelsey L. Merlo, Howard M. Weiss 654 Cherry St NW Atlanta, GA 30332 P: (404) 385-1954 C: (678) 687-2816 E: WorkExperienceResearch ….@psych.gatech.edu - Having specific goals may help maintain attention and help individuals complete a task. - According to Locke and Latham (1990), three mechanisms explain the effect of goals on performance: effort, persistence, and direction of attention. - Specific and difficult goals are able to redirect attention to goal-relevant stimuli. CURRENT STUDY - The Sustained Attention to Response Task (SART) involves withholding a response to rare target (i.e., 1 out of 9 trials) (Robertson et al., 1997). - SART manipulates goals by instructing the participants to strive for a specific goal or simply perform their best (Robertson et al., 1997). - Performance on the SART will be used to assess the attentional pull of each assigned goal condition Figure 1. Target v. Non-target Statistics * H1 : t(17) = 2.376, p < 0.05 H2 : t(17) = -0.059, p = 0.954 - A significant difference was found in the mean values of target trial performance between the two conditions (specific and difficult v. do-your-best). - No significant difference was found between the two conditions in the mean values of non-target trial performance 0 0.2 0.4 0.6 0.8 1 1.2 Specific and difficult Do-your-best Mean Goal Conditions Accuracy of Goal Condition Comparison Target trials Non-target trials H2 *H1 Target Trials Non-Target Trials Mean Standard Deviation Mean Standard Deviation Specific and difficult 0.662 0.208 0.988 0.051 Do-your-best 0.444 0.192 0.973 0.024 Table 1 Statistics for Accuracy on Target and Non-Target Trials buffalo Animal Accuracy 50.00% Correct Vegetable Accuracy 33.33% Correct Animal Accuracy 50.00% Correct Vegetable Accuracy 33.33% Correct XXXXXXXXXXXX onion Animal Accuracy 50.00% Correct Vegetable Accuracy 33.33% Correct Mean Standard Deviation Specific and difficult 3.178 0.795 Do-your-best 3.256 0.385 Table 2 Goal Commitment 9 Items H3 : t(18) = -0.784, p = 0.784 - T-test of difference of means between specific and challenging goal condition v. do-your-best condition was not significant, suggesting that the commitment levels for both conditions are similar.