A Mixed Methods Study of Student Learning Objectives (SLOS) in Evaluating Teacher Effectiveness

Student Learning Objectives (SLOs), as a measure of students’ academic growth, have been broadly used in the evaluation of teacher effectiveness. In this research I employed a mixed-methods sequential explanatory design and incorporated four studies to investigate using SLOs in teacher evaluation in South Carolina (SC). For Study 1 and Study 2, I used surveys to explore educators’ perspectives of SLOs before and after the full implementation of the teacher evaluation system in SC. For Study 3, I used interviews with teachers to explore in-depth the impact and implementation of SLOs. In Study 4, I investigated the relationship between teachers’ SLO scores and classroom observation scores. An analysis of survey scale questions and open-ended questions, interviews, and evaluation scores from a total of 1,020 participants revealed important findings about using SLOs in the evaluation of teacher effectiveness. First, most educators agreed on the impact of SLOs before the full implementation of the evaluation system but disagreed on the impact of SLOs after the full implementation of the system. Second, most educators agreed on the impact of classroom observations both before and after the full implementation of the evaluation system. Third, in comparison with teachers, administrators reported more positive views of both SLOs and classroom observations. Fourth, after the full implementation of the evaluation system, early career teachers reported more positive views of both SLOs and classroom observations in comparison with career teachers. In addition, there were various issues reported regarding the implementation of SLOs in teacher evaluation. Finally, teachers who had positive views of classroom observations tended to have more positive views of SLOs. Teachers who had a higher classroom observation score tended to have a higher SLO score, and the SLO scores could better differentiate teacher performance in comparison with their classroom observation scores. These findings provide important information about using SLOs in teacher evaluation in South Carolina. They can be used to improve teacher evaluation system, inform policy making, promote teacher professional development, enhance classroom instruction and assessment, and support student learning

A Comparison of Assessment Book Authors’ and Educators’ Perspectives on Ethics Issues in Assessment: A Review Study

Assessment book authors’ perspectives on ethical assessment practices are not necessarily consistent with those of educators. This study’s purpose was to explore similarities and differences between the two perspectives. Researchers presented scenarios of classroom assessment practices to gain insights into educators’ perspectives on ethical issues. Fourteen scenarios that were common across three empirical research articles were selected. Educators had similar opinions on a scenario if 70% or more respondents selected “ethical” or “unethical” on one item. Twenty-five assessment-related books were reviewed to present the authors’ views on the ethicality of classroom assessment practices. The results showed that assessment book authors and educators held similar views on five of the 14 scenarios. Findings might inform the professional development of in-service teachers and the training of pre-service teachers. The results can inform assessment book authors in the future development to address ethics issues in assessment and practitioners in educational technology to consider ethical issues in the process of designing assessment tasks

Review and Classification of Bio-inspired Algorithms and Their Applications

Scientists have long looked to nature and biology in order to understand and model solutions for complex real-world problems. The study of bionics bridges the functions, biological structures and functions and organizational principles found in nature with our modern technologies, numerous mathematical and metaheuristic algorithms have been developed along with the knowledge transferring process from the lifeforms to the human technologies. Output of bionics study includes not only physical products, but also various optimization computation methods that can be applied in different areas. Related algorithms can broadly be divided into four groups: evolutionary based bio-inspired algorithms, swarm intelligence-based bio-inspired algorithms, ecology-based bio-inspired algorithms and multi-objective bio-inspired algorithms. Bio-inspired algorithms such as neural network, ant colony algorithms, particle swarm optimization and others have been applied in almost every area of science, engineering and business management with a dramatic increase of number of relevant publications. This paper provides a systematic, pragmatic and comprehensive review of the latest developments in evolutionary based bio-inspired algorithms, swarm intelligence based bio-inspired algorithms, ecology based bio-inspired algorithms and multi-objective bio-inspired algorithms

Exploring the Relationship between Transport Interventions, Mode Choice, and Travel Perception: An Empirical Study in Beijing, China

Transport interventions help to facilitate the sustainable travel behavior. The effects of transport interventions on travel choices have been addressed extensively. However, little research has been devoted to the influence of transport interventions and travel choice on travel perception. This study aimed to investigate the relationship among the three aspects. Two intervention measures, information intervention and public transport service improvement, were selected. Intervention experiments were designed to collect mode choice and corresponding travel perception in different experiment stages. Process models of information intervention and public transport service improvement were proposed. The results show that information intervention only had a minor effect on mode choice and had no direct effect on travel perception. Public transport service improvement in in-vehicle time and comfort enhanced public transport use dramatically. Comfort improvement also had positive effects on travel perception. Walking had positive and public transport trips had negative effects on travel perception. For travelers who had a high evaluation of car trips, the probability of green mode use would decrease. Travelers who gave high marks to trips by green mode would have a higher probability to keep traveling by green mode. This study contributes to facilitating public transport use and enhancing positive perception during traveling

What Motivates Drivers to Comply with Speed Guidance Information at Signalized Intersections?

This study explored the intrinsic motivation of drivers most likely to accept guidance information at signalized intersections by using a mixed model approach. The proposed approach contains a multiple-indicator multiple-cause model (MIMIC) with a latent class analysis (LCA). The MIMIC model was used to quantify intrinsic motivations according to individual heterogeneity. From a group similarity perspective, the LCA was employed for the latent classification of drivers. The features and possibility of accepting guidance information of each class were also analyzed according to the intrinsic motivation of drivers. Data were collected from the stated preference online surveys, in which the questionnaire was designed according to the diffusion of innovation, in 2015 and 2019 in China. Four subjective perceptions of drivers were identified: the perception of innovating guidance information, the perception of convenience regarding guidance information transmission, the perception of surrounding complexity, and the individual innovation. The estimation results show that age, driving experience, education levels, and familiarity with road network are significant factors of compliance behavior. The proportion of conservatives gradually decreased from 2015 to 2019, while the proportion of early followers and late followers increased through market penetration, familiarity with the Internet of vehicles, and social networks in the same period. This prevalence demonstrates that guidance information at signalized intersections is gradually becoming acceptable in China

What Factors Contribute to Higher Travel Happiness? Evidence from Beijing, China

Travel happiness has drawn increasing attention in recent years. However, the empirical research in developing countries’ context is very limited, and few studies consider both cognitive and affective evaluations during traveling. This study uses web-based survey data collected in Beijing, China, and applies multiple regression analysis to examine impacts of sociodemographic attributes, travel characteristics, residential environment, mode consonance, self-evaluation, and health conditions, on travel happiness. Satisfaction with Travel Scale (STS) is used to measure travel happiness. Results show that for trips using active travel modes, traveling by walking has higher travel happiness than by nonmotor vehicles. For those trips traveling by motor vehicles, company shuttle bus trips have the highest travel happiness ratings, followed by automobile trips and public transport trips. Transport mode consonance is significantly positively correlated with travel happiness. Residential environment, self-reported optimism, and daily happiness have great positive impacts on travel happiness. Living in suburban areas is more satisfying for walking and car trips, but travel frequency, travel duration, and perceived travel time length have significant negative effects on travel happiness. Public transport use with friends is enjoyable, but unpleasant with work partners. More happiness when listening to music/radio or reading during traveling is demonstrated. Finally, policy implications and potential extended research topics are recommended

How Have Travelers Changed Mode Choices for First/Last Mile Trips after the Introduction of Bicycle-Sharing Systems: An Empirical Study in Beijing, China

In recent years, there has been rapid development in bicycle-sharing systems (BSS) in China. Moreover, such schemes are considered promising solutions to the first/last mile problem. This study investigates the mode choice behaviors of travelers for first/last mile trips before and after the introduction of bicycle-sharing systems. Travel choice models for first/last mile trips are determined using a multinomial logit model. It also analyzes the differences in choice behavior between the young and other age groups. The findings show that shared bicycles become the preferred mode, while travelers preferred walking before bicycle-sharing systems were implemented. Gender, bicycle availability, and travel frequency were the most significant factors before the implementation of bicycle-sharing systems. However, after implementation, access distance dramatically affects mode choices for first/last mile trips. When shared bicycles are available, the mode choices of middle-aged group depend mainly on gender and access distance. All factors are not significant for the young and aged groups. More than 80% of public transport travelers take walking and shared bicycles as feeder modes. The proposed models and findings contribute to a better understanding of travelers’ choice behaviors and to the development of solutions for the first/last mile problem

Investigating heterogeneity in travel behaviour change when implementing soft transport interventions: A latent class choice model

Abstract Attracting more travellers to shift towards green modes plays a significant role in sustainable transportation development. Soft transport interventions are important strategies for facilitating voluntary travel behaviour change. This study investigates the effects of two soft transport interventions, information intervention and public transport service improvement, on heterogeneous traveller groups’ behaviour change. Beijing, China was selected as the case study site. Firstly, three heterogenous traveller groups were identified based on latent class cluster analysis: Group A (20.4%, travel in low‐frequency and prefer multimode), Group B (30.3%, travel in middle‐frequency and prefer the car) and Group C (49.3%, travel in high frequency and prefer green modes). Then, latent class choice models under two transport interventions were established respectively. The findings indicate that information intervention decreases Group B's preference for car use and exclusion of bicycles. Little effect is observed on travel behaviour change of Group A and C. Public transport service improvement significantly reduces car use of Group B and C. This study demonstrates a limited influence of information intervention on travel behaviour change and public transport service improvement is effective in achieving car use reduction. The results provide decision makers with the information needed to target interventions for different traveller groups

Transcriptomic divergence of the Rheum palmatum complex derived from top-geoherb and non-geoherb areas provides the insights into geoherbalism properties of rhubarb

Abstract Geoherb usually represents high-quality medicinal herbs with better clinical therapeutic effects, and elucidating the geoherbalism is essential for the quality improvement of traditional Chinese Medicine. However, few researches were conducted to clarify the geoherbalism based on a large scale of transcriptomics. In the present study, we compared the transcriptomes of Rheum palmatum complex derived from top-geoherb and non-geoherb areas to show the geoherbalism properties of rhubarb. A total of 412.32 Gb clean reads were obtained with unigene numbers of 100,615 after assembly. Based on the obtained transcriptome datasets, key enzyme-encoding genes involved in the anthraquinones biosynthesis were also obtained. We also found that 21 anthraquinone-related unigenes were differentially expressed between two different groups, and some of these DEGs were correlated to the content accumulation of five free anthraquinones, indicating that the gene expression profiles may promote the geoherbalism formation of rhubarb. In addition, the selective pressure analyses indicated that most paired orthologous genes between these two groups were subject to negative selection, and only a low proportion of orthologs under positive selection were detected. Functional annotation analyses indicated that these positive-selected genes related to the functions such as gene expression, substance transport, stress response and metabolism, indicating that discrepant environment also enhanced the formation of geoherbalism. Our study not only provided insights for the genetic mechanism of geoherbalism of rhubarb, but also laid more genetic cues for the future rhubarb germplasms improvement and utilization