EFFECTS OF VIDEO-ASSISTED TRAINING ON EMPLOYMENT-RELATED SOCIAL SKILLS OF ADULTS WITH SEVERE MENTAL RETARDATION

Two studies investigated effects of video-assisted training on employment-related social skills of adults with severe mental retardation. In video-assisted training, participants discriminated a model's behavior on videotape and received feedback from the trainer for responses to questions about video scenes. In the first study, 3 adults in an employment program participated in video-assisted training to request their supervisor's assistance when encountering work problems. Results indicated that participants discriminated the target behavior on video but effects did not generalize to the work setting for 2 participants until they rehearsed the behavior. In the second study, 2 participants were taught to fix and report four work problems using video-assisted procedures. Results indicated that after participants rehearsed how to fix and report one or two work problems, they began to fix and report the remaining problems with video-assisted training alone.     

Using item-specific instructional information in achievement modeling

The problem of detecting instructional sensitivity (item basis) in test items is considered. An illustration is given which shows that for tests with many biased items, traditional item bias detection schemes give a very poor assessment of bias. A new method is proposed instead. This method extends item response theory (IRT) by including item-specific auxiliary measurement information related to opportunity-to-learn. Item-specific variation in measurement relations across students with varying opportunity-to-learn is allowed for.This paper was presented at the 1987 AERA meeting in Washington, DC. This research was supported by grant OERI-G-86-003 from the Office of Educational Research and Improvement, Department of Education. The author thanks Michael Hollis and Chih-fen Kao for valuable research assistance, and appreciates valuable comments made by an anonymous reviewer.     

TEACHING AUTISTIC CHILDREN CONVERSATIONAL SPEECH USING VIDEO MODELING

We assessed the effects of video modeling on acquisition and generalization of conversational skills among autistic children. Three autistic boys observed videotaped conversations consisting of two people discussing specific toys. When criterion for learning was met, generalization of conversational skills was assessed with untrained topics of conversation; new stimuli (toys); unfamiliar persons, siblings, and autistic peers; and other settings. The results indicated that the children learned through video modeling, generalized their conversational skills, and maintained conversational speech over a 15-month period. Video modeling shows much promise as a rapid and effective procedure for teaching complex verbal skills such as conversational speech.     

Parent and child adjustment dual trajectories at the beginning of the COVID-19 syndemic

Children and their families have been significantly impacted by the unfolding of the COVID-19 syndemic. We sought to identify (1) groups of families with distinct profiles of joint trajectories of parental anxiety and child emotional distress and (2) protective and risk factors associated with these dual-trajectory profiles. A sample of 488 parents (65% White; 77% mothers) with 3- to 8-year-old children (M_Age = 5.04, SD_Age = 1.59) was followed from late March to early July in 2020. Survey data on parent (i.e., anxiety symptoms) and child (i.e., emotional distress) adjustment were collected at three time points. Using multivariate growth mixture modeling, we identified one group with low parental anxiety and child emotional distress (42.7%) and three other distinct groups with varying risk levels among parents and/or children. We also identified protective (e.g., positive parenting) and risk (e.g., child negative affect, negative parenting, perceived stress with racism) factors in predicting parent and child adjustment. It can be concluded that, overall, our sample (mostly middle- and high-socioeconomic status families) demonstrated family resilience amid COVID-19, consistent with prior disaster coping literature. At the same time, our findings also indicated the need to identify at-risk families and modifiable factors for post-disaster public health interventions.     

French validation of the Twenty-Item Value Inventory

IntroductionPersonal values are important for understanding psychological phenomena by serving as predictors of individuals’ attitudes and behavior. The Twenty-Item Value Inventory (TwIVI, Sandy et al., 2017) was developed to assess values with items from the Portrait Values Questionnaire (PVQ, Schwartz et al., 2001).ObjectiveThe goal of this study was to assess the reliability and validity of the French version of the TwIVI.MethodTwo French-Canadian samples of adults (N1 = 825; N2 = 429) were recruited in order to test the reliability and validity of the TwIVI.ResultsResults revealed that the French version of the TwIVI showed satisfying temporal stability, convergence validity with the PVQ, and concurrent validity with personality traits. Some issues were observed for internal consistency and structural validity, assessed with both multidimensional scaling and exploratory structural equation modeling.ConclusionOverall, these findings partially support the psychometric qualities of the French version of the TwIVI. Implications for theory and research on values are discussed.     

How infant-directed actions enhance infants’ attention,learning, and exploration: Evidence from EEG and computational modeling

When teaching infants new actions, parents tend to modify their movements. Infants prefer these infant-directed actions (IDAs) over adult-directed actions and learn well from them. Yet, it remains unclear how parents’ action modulations capture infants’ attention. Typically, making movements larger than usual is thought to draw attention. Recent findings, however, suggest that parents might exploit movement variability to highlight actions. We hypothesized that variability in movement amplitude rather than higher amplitude is capturing infants’ attention during IDAs. Using EEG, we measured 15-month-olds’ brain activity while they were observing action demonstrations with normal, high, or variable amplitude movements. Infants’ theta power (4–5 Hz) in fronto-central channels was compared between conditions. Frontal theta was significantly higher, indicating stronger attentional engagement, in the variable compared to the other conditions. Computational modelling showed that infants’ frontal theta power was predicted best by how surprising each movement was. Thus, surprise induced by variability in movements rather than large movements alone engages infants’ attention during IDAs. Infants with higher theta power for variable movements were more likely to perform actions successfully and to explore objects novel in the context of the given goal. This highlights the brain mechanisms by which IDAs enhance infants’ attention, learning, and exploration.     

Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.     

Using self-evaluation to improve difficult-to-read handwriting of secondary students

We used delayed multiple-baseline and multiple-probe techniques to assess the effects of self-evaluation training on the legibility of cursive handwriting. Five secondary special education students with difficult-to-read handwriting served as participants. All participants improved the legibility of their handwriting during self-evaluation training. A systematic withdrawal of the training package demonstrated maintenance of treatment effects. For the most part, the students' handwriting remained at least 90% legible to judges following the systematic withdrawal of the self-evaluation training.     

Modeling item responses when different subjects employ different solution strategies

A model is presented for item responses when different subjects employ different strategies, but only responses, not choice of strategy, can be observed. Using substantive theory to differentiate the likelihoods of response vectors under a fixed set of strategies, we model response probabilities in terms of item parameters for each strategy, proportions of subjects employing each strategy, and distributions of subject proficiency within strategies. The probabilities that an individual subject employed the various strategies can then be obtained, along with a conditional estimate of proficiency under each. A conceptual example discusses response strategies for spatial rotation tasks, and a numerican example resolves a population of subjects into subpopulations of valid responders and random guessers.The first author's work was supported by Contract No. N00014-85-K-0683, project designation NR 150-539, from the Cognitive Science Program, Cognitive and Neural Sciences Division, Office of Naval Research. We are grateful to Murray Aitkin, Isaac Bejar, Neil Dorans, Frederiksen, and Marklyn Wingersky for their comments and suggestions, and to Alison Gooding, Maxine Kingston, Donna Lembeck, Joling Liang, and Kentaro Yamamoto for their assistance with Example 2.     

Finite mixtures in confirmatory factor-analysis models

In this paper, various types of finite mixtures of confirmatory factor-analysis models are proposed for handling data heterogeneity. Under the proposed mixture approach, observations are assumed to be drawn from mixtures of distinct confirmatory factor-analysis models. But each observation does not need to be identified to a particular model prior to model fitting. Several classes of mixture models are proposed. These models differ by their unique representations of data heterogeneity. Three different sampling schemes for these mixture models are distinguished. A mixed type of the these three sampling schemes is considered throughout this article. The proposed mixture approach reduces to regular multiple-group confirmatory factor-analysis under a restrictive sampling scheme, in which the structural equation model for each observation is assumed to be known. By assuming a mixture of multivariate normals for the data, maximum likelihood estimation using the EM (Expectation-Maximization) algorithm and the AS (Approximate-Scoring) method are developed, respectively. Some mixture models were fitted to a real data set for illustrating the application of the theory. Although the EM algorithm and the AS method gave similar sets of parameter estimates, the AS method was found computationally more efficient than the EM algorithm. Some comments on applying the mixture approach to structural equation modeling are made.Note: This paper is one of the Psychometric Society's 1995 Dissertation Award papers.—EditorThis article is based on the dissertation of the author. The author would like to thank Peter Bentler, who was the dissertation chair, for guidance and encouragement of this work. Eric Holman, Robert Jennrich, Bengt Muthén, and Thomas Wickens, who served as the committee members for the dissertation, had been very supportive and helpful. Michael Browne is appreciated for discussing some important points about the use of the approximate information in the dissertation. Thanks also go to an anonymous associate editor, whose comments were very useful for the revision of an earlier version of this article.