Browsing by Subject "measurement"

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Aprendizaje invisible: Hacia una nueva ecología de la educación
(Laboratori de Mitjans Interactius / Publicacions i Edicions de la Universitat de Barcelona, 2011-04-15) Cobo, Cristóbal; Moravec, John W.
The proposed invisible learning concept is the result of several years of research and work to integrate diverse perspectives on a new paradigm of learning and human capital development that is especially relevant in the context of the 21st century. This view takes into account the impact of technological advances and changes in formal, non-formal, and informal education, in addition to the 'fuzzy' metaspaces in between. Within this approach, we explore a panorama of options for future development of education that is relevant today. Invisible Learning does not propose a theory, but rather establishes a metatheory capable of integrating different ideas and perspectives. This has been described as a protoparadigm, which is still in the 'beta' stage of construction.
Data from Liking of Food Textures and Relationship with Oral Physiological Parameters, Part 2
(2016-08-23) Kim, Sophia C; kimx1564@umn.edu; Kim, Sophia C
The data from Part 2 of the thesis "Liking of Food Textures and Relationship with Oral Physiological Parameters,"contains the raw and processed data files in which participants evaluated their liking of 106 texture attributes and then classified themselves into one of the mouth behavior groups. The saliva flow rate, biting force, variance of hue, and particle size difference threshold of each participant were also measured. Age and gender information is also included. The data can be used for various analyses in order to examine the relationships among the different types of variables.
Direct Observational and Biological Measurement of Reactivity to Sensory Stimuli for Use with and without Developmental Disabilities
(2024-08) Worthley, Emma
Given the inclusion of sensory reactivity as a diagnostic criterion for autism spectrum disorder (ASD) and the theorized etiological role of sensory reactivity in the development of autism, adequate sensory measures of sensory reactivity in autism, including measures extending to use in infancy, are needed. Adequate sensory measurement relies on the use of multiple methods of measurement. A scoping review of direct observational and biological measures of responses to sensory stimuli was conducted to identify plausible direct observational and biological measures of sensory reactivity for use with autistic samples. A direct observational measure of sensory reactivity was identified in the scoping review (a modified quantitative sensory testing approach) and implemented in two empirical investigations with different samples. The modified quantitative sensory testing approach was undertaken with a sample of children with and without autism (n=45, including eight autistic children) to investigate differences in tactile reactivity between children with and without autism. The modified quantitative sensory testing approach was then undertaken with a sample of typically developing children (n=34) to explore the relationship between subjective experience of tactile stimuli and behaviorally observed tactile reactivity. Through the scoping review, 111 articles reporting the use of a direct observational or biological sensory measure were identified, including 53 articles describing the use of behavioral measures of sensory reactivity, 18 articles describing the use of peripheral nervous system physiology measures of sensory reactivity, 47 articles describing the use of central nervous system physiology measures of sensory reactivity, and eight articles describing the use of circuits of sensory reactivity. The use of direct observational measure, the modified Quantitative Sensory Test (mQST), identified differences in tactile reactivity to four tactile stimuli (light touch, pinprick, the last five seconds of the repeated von Frey, and heat), such that autistic children tended to demonstrate greater behavioral reactivity in response to these stimuli. The use of the mQST with typically developing children to interrogate the subjective experience of the mQST stimuli via self-report yielded negligible to weak correlations between subjective experience and direct observation of behavioral reactivity in response to the tactile stimuli but did, however, yield validity evidence for the use of the mQST in typically developing children. Overall, a wide variety of direct observational and biological sensory measures are available for use in autism research, with the potential to shed light on underlying mechanisms explaining differences in overt sensory behaviors.
Experimental Cascade Simulation of First Stage High Pressure Gas Turbine with Effects of Leakage Flow and Contouring on Endwall Film Cooling
(2015-06) Saxena, Reema
Flow in a high pressure gas turbine passage is complex involving systems of secondary vortex flows. This complexity causes difficulty in providing film cooling coverage to the thermally loaded hub endwall region. An improved understanding of the effect of these flow features on endwall heat transfer is needed to assist designers in developing efficient cooling schemes. The present experimental study is performed in a linear, stationary cascade with a contoured endwall, representing first stage stator of a high pressure gas turbine. Passage thermal fields and endwall adiabatic effectiveness values are measured. Engine representative conditions such as high free stream turbulence, large eddies, high Reynolds number, varying coolant mass flow ratios, and non-uniform approach flow temperature profiles are set up. Results show that the combined effect of slot geometry, endwall profile shape, and coolant mass and momentum flux ratio, is an important determinant in assessing film cooling effectiveness.
Exploring Alternate Latent Trait Metrics with the Filtered Monotonic Polynomial IRT Model
(2016-07) Feuerstahler, Leah
Item response theory (IRT) is a broad modeling framework that makes precise predictions about item response behavior given individuals’ locations on a latent (unobserved) variable. If the item-trait regressions, also known as item response functions (IRFs), are monotonically increasing and if assumptions about unidimensionality and local independence are satisfied, then examinees can be ordered uniquely on the latent trait. Scales that satisfy these three assumptions can be transformed monotonically without altering scale properties—that is, they define an ordinal-level scale (Stevens, 1946). When fitting an IRT model, however, the scale of the latent variable—that is, its location and interval spacing—must be identified by introducing extra assumptions. In practice, the scale is identified by specifying either the parametric form of the IRF (parametric IRT) or the distribution of the latent trait (nonparametric IRT). Filtered monotonic polynomial IRT (FMP) has been proposed as a type of nonparametric IRT method (Liang & Browne, 2015), but shares important properties with parametric methods. In this dissertation, it is demonstrated that any IRF defined within the FMP framework can be re-expressed as another FMP IRF by taking linear or nonlinear transformations of the latent trait. A general form for these transformations is presented in terms of matrix algebra. Finally, I propose a composite FMP IRT model in which nonlinear transformations of the latent trait are modeled explicitly by a monotonic composite function.I argue that the composite model offers many advantages over existing methods. First, the composite FMP model narrows the methodological gap between para- metric and nonparametric item response models, allowing for item banking and adaptive testing within a flexible modeling framework. Second, this composite model suggests a sequential NIRT curve-fitting method that allows users to explore both alternate (e.g., non-normal) latent densities and flexible IRF shapes. Finally, the composite FMP model allows users to explore and employ alternate scalings of the latent trait without sacrificing the methodological advantages of parametric models.
Innovative Approaches to Substance Use Measurement: Questionnaires, Screening Tools, and Smartwatch Algorithms
(2024-07) Bush, Nicholas
Alcohol and cannabis are two of the most widely used substances in the United States and are associated with significant public health costs. Alcohol and cannabis-related health consequences have also been increasing over the past 10 to 15 years. However, despite the increased prevalence, our ability to assess and treat individuals has stagnated. This is likely due to three main reasons: 1) a limited ability to screen individuals at risk, especially in relation to co-morbid conditions like chronic pain, 2) the increased variety of available substance products (i.e., cannabis flower vs concentrates), dosages, and ways to divide such products (i.e., drinks, grams, ounces), and 3) significant barriers to accessibility of substance-related treatment. The goals of the dissertation were to develop and validate innovative methodologies to address the identified gaps in the literature. First, we developed a brief clinical screening tool to assess risk of self-medication of pain with substance use. We used an iterative process to reduce the total number of items from 104 to a 14-item and 7-item version. We found that both versions were significantly associated with self-medication behavior and substance use health risks, with minimal differences between the two versions. Second, we modified an existing behavioral economics measure to adapt to a user’s specified preferred product (e.g., dried flower) and division method (e.g., hits or grams). The modified behavioral economics measure demonstrated convergent validity and strong criterion validity compared to the original. In addition, we demonstrated significant differences associated with user preferences, such that individuals with a preference for dried flowers showed greater demand than those with a preference for concentrations. Third, we developed a novel smartwatch algorithm in an accessible framework to detect and analyzing drinking behavior. This technology provides the technological foundation for the development of accessible just-in-time alcohol use interventions. We compared the performance of a distribution-based algorithm to a traditional machine learning model in a controlled paced drinking environment. Our distributional sip detection algorithm performed similarly to our ground truth on our behavioral outcomes (i.e., sip duration, sip interval, and number of sips). It also performed significantly better than a random forest machine learning classification model. Lastly, we validated our automatic sip detection algorithm using a simulated virtual reality bar environment to allow unrestricted drinking with validated ground truth measures. We found that the algorithm had moderate-to-high classification with our ground truth measures. In conclusion, the results from these studies provide important methodological tools designed to increase the field’s ability to develop innovative and accessible methodologies. This work will also provide the support to enhance the assessment of substance use mechanisms by improving our ability to screen, adapt and develop accessible frameworks for interventions.
Knowledge As A Foundation For Performance Measurement
(2016-05) Boyce, Tamra
Findings showed that one of the program metrics (teach clients three marketable skills) was significantly associated with overall ratings of program quality. The validity of this individual program element as an indicator for evaluating program quality is supported by the results of a regression analysis. The findings failed to support the thesis that employment programs that address learned helplessness are rated higher than employment programs that do not address learned helplessness. Among these decision makers, there is a preference for program activities that focus on job experience and skill development.
A precision measurement of the Higgs boson mass in the diphoton decay channel
(2024-07) Schroeder, Neil
A measurement of the mass of the Higgs boson has been performed in the diphoton decay channel. This analysis is based on 138 fb⁻¹ of pp collision data collected in 2016-2018 with the CMS detector at the LHC at a center-of-mass energy of 13 TeV. The mass is measured to be 𝐦𝐇 = 125.574 ± 0.088 (stat.) ± 0.121 (syst.) GeV. This thesis summarizes the strategy of this measurement with emphasis on the methods employed to mitigate and quantify the main sources of systematic uncertainty.
Psychometric Evaluation of Social and Emotional Learning Measures Using Multidimensional Item Response Theory Models
(2022-11) Kang, Youngsoon
Social and emotional learning (SEL) has become essential in educational settings and human development. Federal policy has begun to incorporate SEL factors into education accountability metrics. Schools, institutes, and scholars have started implementing SEL in K-12 educational contexts. Social interactions and emotions are a daily part of students’ lives, both in and out of school, which is why many educators are willing to teach and measure SEL competencies. Moreover, in previous research, it has been found that students’ higher SEL competencies are positively associated with higher academic performance and lower risky behaviors. As interest in SEL grows, measurement tools continue to evolve. An interesting finding from the overview of existing SEL measures was that not only a general SEL scale is measured but in practice, multiple dimensions, or subscales of SEL. This finding implies the multidimensional nature of SEL measures. How- ever, researchers have not attempted to use the multidimensional item response theory to identify the multidimensionality of SEL measures and evaluate their psychometric properties. This dissertation aimed to apply MIRT models to the MSS-SEL data, identify the best-fitting model, and conduct a psychometric evaluation of the MSS-SEL items and dimensions. To mediate person-score calibration and evaluation, psychometric properties such as internal structure and item parameter estimates of the MSS-SEL items were evaluated under MIRT framework. The results showed that among the competing correlated models, MGRM fitted better than the MG- PCM to the MSS-SEL data. Additionally, among the competing bifactor models, bifactor-GRM fitted better than the bifactor-GPCM. The results indicated that for both the correlated MIRT model and bifactor model applications, the graded response modeling approach functioned better for the MSS-SEL response data than the generalized partial credit modeling approach. The results of the MGRM application showed that some MSS-SEL factors were relatively more highly correlated than others. One of the bifactor-GRM results showed that the general factor (i.e., SEL) accounted for by 66% of the common variance among items. Each specific factor was accounted almost equally well for the rest of the variance. Overall, the 37 SEL items reflected the general factor reasonably well, and most of the items were moderately/strongly explained by the general factor.This dissertation demonstrated what could have been missed if just a single model (i.e., UIRT, correlated MIRT model, or bifactor model) was fitted to the data. Furthermore, validity evidence was provided for the potential use and interpretation of the MSS-SEL scores. Several implications can be made especially for researchers and practitioners who frequently get involved in all different phases of SEL measurement. First, it is important to plan ahead for an item and scale development and to search for theoretically suitable IRT models. Second, it is crucial to examine the internal structure and use MIRT models when there are multiple SEL constructs to be measured. Third, the types of scores that are meaningful for the report and to be used should be clearly declared by the SEL measurement developers and users. Psychometric evaluation of the existing SEL measures using relevant measurement models will contribute to the validation of the SEL measures in support of the intended interpretation and use of such measures by educators and practitioners. This, of course, is a core component of validity evidence to interpret and use SEL scores at multiple levels. Moreover, this is a part of a larger effort to understand and articulate a set of psychometric principles for SEL measurement.
Robot-Aided Assessment of Ankle Motion Sense and Associated Lesion-Symptom Mapping Analysis in Chronic Stroke
(2023-06) Huang, Qiyin
Background: Compromised ankle proprioception is a strong predictor of balance dysfunction in chronic stroke. However, objective, accurate methods for testing ankle proprioceptive function in clinical settings are not established. Only sparse data on ankle position sense and no systematic data on ankle motion sense dysfunction in stroke are available. Moreover, the lesion sites underlying impaired ankle proprioception have not been comprehensively delineated.Objectives: To address these knowledge gaps, this study aimed: 1) To examine the feasibility and test-retest reliability of a newly developed robotic technology that uses an adaptive psychophysical forced-choice method to obtain quantitative data on ankle position and motion sense acuity in healthy young adults. 2) To determine the extent and magnitude of ankle motion sense impairment observed in adults with chronic stroke and how such impairment coincides with position sense dysfunction using the robotic system. 3) To identify the brain lesions associated with ankle position and motion sense dysfunction. Methods: To verify aim 1, experiments 1 and 2 were conducted successively. Forty healthy adults (20 in each experiment, mean ± SD age 24 ± 3.9 years, F: 17) were recruited. The feasibility and test-retest reliability of the system were determined in Experiment 1. Experiment 2 was conducted to improve the motion sense test paradigm that controlled for confounding factors (time and position) that a person might use as motion cues to make a perceptual judgment of ankle joint motion. To verify aim 2 and 3, twelve stroke survivors (mean ± SD age, 54 ± 10.9 years, on average 6 years post-stroke, 10 ischemic, 2 hemorrhagic lesions), and 13 neurotypical adults participated. During the testing, the robot passively plantarflexed a participant’s ankle to two distinct positions or at two distinct velocities. Participants subsequently indicated which of the two movements was further/faster. Based on the stimulus-response data, a psychometric function was obtained, and just-noticeable-difference (JND) thresholds, as a measure of bias, and intervals of uncertainty (IU), as a measure of precision were derived. For adults with stroke (n = 11), lesion-symptom analyses identified the brain lesions associated with observed proprioceptive deficits in adults with stroke. Results: For aim 1, objective data on position sense acuity (JND threshold: 0.80° ± 0.10°, IU: 0.84° ± 0.41°) and motion sense acuity (JND threshold: 0.73°/s ± 0.11°/s, IU: 0.60°/s ± 0.29°/s) were obtained in experiment 1. Additionally, moderate-to-excellent test-retest reliability of the system has been established based on the JND threshold for position sense (average intraclass correlation coefficient (ICC) = 0.86 [0.50 - 0.98], standard error of measurement (SEM) = 0.0173°) and motion sense (average ICC = 0.88, SEM = 0.0197°/s). In experiment 2, the results showed that the mean JND motion sense threshold increased almost linearly from 0.53°/s at the 10°/s reference to 1.6°/s at 20°/s (p < 0.0001). Perceptual uncertainty increased similarly (median IU = 0.33°/s at 10°/s and 0.97°/s at 20°/s; p < 0.0001). Both measures were strongly correlated (rs = 0.70). For aim 2, 83% of adults with stroke exhibited abnormalities in either position or motion sense, or both. JND and IU measures were significantly elevated compared to the control group (JNDPosition: +77%, p = 0.03; JNDMotion: +153%, IUPosition: +148%, and IUMotion: +78%, all p < 0.01). The JND and IU values of both senses were strongly positively correlated (rs = 0.56-0.62). For aim 3, lesions in the primary somatosensory, posterior parietal, motor cortices, insula, and temporoparietal regions (supramarginal, superior temporal, Heschl's gyri) were associated with deficits in both senses. Meanwhile, lesions in the medial/lateral occipital cortex were linked to impaired position sense, and temporal pole lesions were associated with impaired motion sense. Moreover, temporal pole lesions were significantly related to motion sense deficit (z-score = 3.26). Conclusion: This research demonstrated that the proposed robot-aided test produces quantitative data on human ankle position and motion sense acuity. It yields two distinct measures of proprioceptive acuity (i.e., bias and precision) as part of a comprehensive analysis of proprioceptive function. Using the robot-aided assessment, this study documented the initial data on the magnitude and prevalence of ankle position and motion sense impairment in adults with chronic stroke. Proprioceptive dysfunction was characterized by elevated JND thresholds and increased uncertainty in perceiving ankle position/motion. Associated cortical lesions for both proprioceptive senses were largely overlapping, but temporal pole lesions were independently linked to motion sense dysfunction.
Using psychometric models to measure social and emotional learning constructs
(2020-08) Smith, Mireya
In Testing Standards (2014), a construct is a concept or characteristic that an assessment is intended to measure. From a quantitative lens, a construct is trait or domain that may include attitudes, skills, abilities, dispositions and some aspects of knowledge (e.g., competencies). Research studies suggest that social and emotional learning (SEL) constructs may be useful in narrowing the achievement gap, however there is no agreed upon definition of SEL as SEL constructs are multifaceted and defined by the researcher(s). Currently, some SEL constructs are measured qualitatively but this ignores the quantitative structure of the construct. In the quantitative field, SEL constructs are measured by applying a less complex model before a complex model. However, this disregards the qualitative definition for the SEL construct. Furthermore, a construct cannot be directly measured (e.g., person’s height), instead, we need to indirectly observe SEL constructs through item responses (e.g., polytomous items). The problem is that there is a lack of clarity in how the SEL constructs are defined and measured. In addition, there is very little research in an approach for SEL constructs to have accumulating evidence that supports score interpretation and use. This study proposes using the paradigm for SEL assessment that can lead to meaningful, useful, appropriate, and fair score interpretation and use. The paradigm consists of three components. The first component, the structural components of SEL, makes a distinction of the units of SEL assessment (framework, construct(s), measure(s) and item responses) where the construct is the centerpiece. The second component is where the construct definition and measurement model work together to put forth plausible competing models for the internal structure (e.g., bifactor) of selected SEL constructs. The final component is forms of validity evidence (e.g., measurement invariance) where the focus is to evaluate the claims (e.g., scores can be compared across groups) regarding what the scores represent and how they should be used. The paradigm for SEL assessment encourages researchers from the qualitative and quantitative fields to work together to properly define SEL constructs in a qualitative (e.g., theory) and quantitative (e.g., confirmatory factor analysis and item response theory models) manner.

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