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The Pediatric Symptom Checklist-17 (PSC-17) is a popular screening instrument used by parents and clinicians to assess children's behavioral functioning. However, more schools are examining the potential of the PSC-17 as part of a Multi-Tier System of Support framework. To investigate the potential of the PSC-17 in the schools, a sample of 1,779 U.S. preschool and kindergarten-aged children rated by parents (n = 667) and teachers (n = 1,112) was used to assess the measurement invariance of the PSC-17 across respondent groups. Multiple-group Confirmatory Factor Analysis supported partial scalar invariance for the PSC-17, indicating functional equivalence across teacher and parent respondents. Latent mean testing revealed teachers rated children as exhibiting a lower level of Externalizing Problems relative to parents; however, no significant differences in children's Internalizing Problems and Attention Problems were found between teacher and parent ratings.

A growing interest has been given to examining the heterogeneity of children's health to provide for their particular needs. This study examined subgroups of elementary school children's social, emotional, and behavioral functioning (SEB) using teacher ratings of children with the Behavioral and Emotional Screening System. A Latent Profile Analysis (LPA) was conducted with 5,150 students aged from kindergarten to fifth grade. Subscale scores in the areas of externalizing risk, internalizing risk, and adaptive skills risk were used to identify profiles. Students' grade level, sex, race, and status of receiving special education services were added to investigate the impact of covariates on the classification of latent profiles. Four profiles of risk were identified: Well Development (60.5%), Normal Development (25.8%), Externalizing and Adaptive Skills Risk (9.1%), and Elevated Risk (4.6%). Significant differences of covariates including sex, race, and status of receiving special education services were identified. Specifically, males and African American students were more likely to be classified into the "Elevated Risk" profile than other profiles. Students who did not receive special education services were more in the "Well Development" profile. The results may have important implications for the stakeholders to allocate intervention and treatment resources effectively and accurately.

Measurement of students' peer assessment motivation is critical to understand how they participate in such activities in higher education. The current study was conducted to develop and validate a brief scale that measures student peer assessment motivation in higher education using the Expectancy-Value Theory (EVT). Initial items were developed, revised, and administered to 369 students. Exploratory factor analyses suggested a three-factor model structure (ability belief, expectancy, and task value) aligning with EVT. Confirmatory factor analyses (n = 399) supported a higher-order factor structure with the three first-order factors (i.e. ability belief, expectancy, and task value) with a decent model fit. The 20-items Peer Assessment Motivation Scale (PAMS) had decent internal reliability, test-retest reliability, convergent validity, and discriminant validity, suggesting that it is a high-quality measure. This scale is beneficial for instructors and researchers who are interested in investigating peer assessment motivation in higher education.

The Pediatric Symptom Checklist-17 was originally used in primary care settings with parents to identify their children's behavioral and emotional problems, but there has been some research supporting use of this scale in school settings. This study examined: (a) the factor structure and measurement invariance of the teacher-rated Pediatric Symptom Checklist-17 and (b) complex relationships among demographic characteristics, behavioral and emotional problems, and learning outcomes using structural equation modeling in elementary schools. A sample of 508 children in grades one and two were rated by their teachers with the Pediatric Symptom Checklist-17. Measures of Academic Progress test was utilized to measure participants' learning outcomes in reading and math. The results confirmed a three-factor structure of the Pediatric Symptom Checklist-17 (internalizing problems, externalizing problems, and attention problems) and attested the measurement invariance across different demographic groups (i.e. gender, ethnicity, and grade levels). Boys were more likely to have severe attention problems which were associated with lower learning outcomes as seen by Measures of Academic Progress reading and math scores. Attention problems mediated the relationship between gender and learning outcomes. This study has implications for the use of the Pediatric Symptom Checklist-17 in school-based settings. Additionally, it highlights the potential relationships among gender, attention problems, and learning outcomes.

Although studies have been conducted on educators' perceptions of assessment practices, few studies explored students' perceptions of the ethical issues in classroom assessment. A mixed design research method was used to examine factors associated with students' perceptions of the ethicality of classroom assessment practices. A sample of 1996 undergraduate students enrolled in 177 colleges and universities in China participated in the quantitative phase of the study to complete a survey measuring students' perceptions regarding the ethicality of classroom assessment. In the qualitative phase, 579 participants responded to the open-ended questions concerning their justification of the ethicality of the individual assessment situations. Quantitative analyses indicated that students' gender, grade level, major, and program were associated with their perceptions of the ethicality of multiple assessment practices (i.e., multiple assessment, surprise items, considering effort and attendance in grading, and giving feedback). Qualitative analyses showed that conflicting needs of different stakeholders in classroom assessment (i.e., student needs vs. assessment needs, teacher needs vs. assessment needs, student needs vs. student needs) were associated with their perceptions. Findings of the current study offer insights for teachers regarding how to make classroom assessment practices ethical based on diverse needs of stakeholders involved in assessment.

Classroom assessment is an effective way to collect evidence about student learning, and a teacher's professional responsibility in assessment is to use high quality, fair, and ethical assessment information to make decisions about students' learning and teachers' instruction. This study used a scenario-based survey and investigated college students' perceptions about the ethicality of classroom assessment practices in Chinese higher education. Participants included 2711 college students from 177 universities located in 23 provinces and 4 municipalities in China. The results revealed that students reported very different levels of agreement with experts on the scenarios, and it appeared to be more challenging for them to recognize unethical assessment practices in comparison with ethical assessment practices. Students valued using multiple assessment methods but reported inconsistent views with experts regarding grading effort. Confidentiality and communication about grading were found to be the key assessment issues to be addressed in Chinese educational context.

Deep neural network (DNN) has been widely used in various artificial intelligence applications and is, unsurprisingly, penetrating the field of school psychology. In the school environment, universal screening is used by teachers to identify children's emotional and behavioral risk (EBR) within a screener. EBR can be used to predict possible emotional and behavioral disorders, which impact children's educational and social outcomes. Using the BASC-2 Behavioral and Emotional Screening System Teacher Rating Scale (BASC-2 BESS TRS; Reynolds & Kamphaus (2004). "Behavior Assessment System for Children" (2nd ed.). Circle Pines, MN: American Guidance Service) norm data, we classified children's EBR status from normal to at-risk using DNN. Data oversampling was used to overcome the imbalanced sample feature (i.e., few cases with emotional and behavioral disorder). Traditional machine learning methods, such as Naïve Bayes and logistic regression, were included for comparison. The results indicated that the DNN with oversampling achieved the highest performance levels with accuracy (ACC) of 0.957, precision (PPV) of 0.545, true positive rate (TPR or sensitivity) of 1.000, and true negative rate (TNR or specificity) of 0.942 compared with the other methods. This novel method is helpful to provide accurate screening results for early identification of children's EBR. The current study provides a useful guide for researchers to apply the DNN and oversampling to classification in assessment-related research.

Positive student attitude towards peer assessment can be demonstrated through high-quality peer assessment activities. Research findings on students' attitudes before and after such activities were mixed. This study was conducted using a mixed-methods approach to investigate the underlying factors influencing students' attitude change. Participants were students enrolled in an online graduate-level assessment course in the college of education in a university in the southeast United States in the fall of 2017 (N = 31). Surveys and interviews were used to collect quantitative and qualitative data separately, both of which indicated that perceived accurate and specific feedback tended to help students shift to more positive attitudes towards online peer assessment. In addition, final task score improvement after the activity was correlated with positive attitude change. Qualitative results also identified other factors, such as communication with the peers' work and logistic concerns. The current study offers insights for researchers and instructors to promote positive attitude changes in online peer assessment activities.

Peer assessment can be conducted online with rapid development of online learning technology. The current study was conducted empirically to investigate peer rating accuracy and student learning outcomes in online peer assessments, comparing compulsory and voluntary peer assessment. Section 1 (N = 93) was assigned to the voluntary group and Section 2 (N = 31) was assigned to the compulsory group. The results showed the voluntary group scored significantly higher than the compulsory group in the final task of the course, while there was no significant difference on the final task score increase. Students who participated in the voluntary group provided more accurate scores (i.e. peer rater accuracy) than those who participated in the compulsory group. The peer score leniency/severity rating, comparing peer assigned scores with the teacher assigned scores, were generally consistent with the peer rater accuracy results. The current study offers insights for researchers who are interested in studying the effect of online peer assessment activities. The results are also of interest for instructors who may want to conduct peer assessments in online courses and are choosing between compulsory and voluntary formats.