排序方式： 共有38条查询结果，搜索用时 860 毫秒
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Gerald G. Strait Jenna Turner Diana Stinson Samanthia Harrison Rojan Bagheri Tanya Perez Bradley H. Smith Jorge Gonzalez Jacqueline R. Anderson Jill Simpson Sam D. McQuillin 《Psychology in the schools》2020,57(9):1492-1505
Many schools use paraprofessionals to implement and monitor interventions. Though paraprofessionals are cost-effective, many questions remain about the training and skills they need to implement a wide array of school-based interventions. In this study, we compare paraprofessionals' (i.e., undergraduates) implementation of the Group-Academic Mentoring Program for Education Development (Group-AMPED) to school psychology graduate students' implementation of Group-AMPED. Ten paraprofessionals and five school psychology graduate students provided approximately eight sessions of Group-AMPED to 35 sixth-grade students. Results indicated no significant differences between middle school students' engagement when groups were led by either school psychology graduate students or paraprofessionals. Similarly, self-reports of fidelity and supervisor postsession implementation confidence indicated no difference between paraprofessionals and graduate students' implementation of Group-AMPED. Follow-up measures indicated that mentors and proteges perceived Group-AMPED as feasible, acceptable, and understandable. Most importantly, middle school students participating in Group-AMPED had significantly higher second-semester grades in comparison to a small control group. 相似文献
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Ebrahim Bagheri Faezeh Ensan Feras Al-Obeidat 《Information processing & management》2018,54(4):657-673
Learning low dimensional dense representations of the vocabularies of a corpus, known as neural embeddings, has gained much attention in the information retrieval community. While there have been several successful attempts at integrating embeddings within the ad hoc document retrieval task, yet, no systematic study has been reported that explores the various aspects of neural embeddings and how they impact retrieval performance. In this paper, we perform a methodical study on how neural embeddings influence the ad hoc document retrieval task. More specifically, we systematically explore the following research questions: (i) do methods solely based on neural embeddings perform competitively with state of the art retrieval methods with and without interpolation? (ii) are there any statistically significant difference between the performance of retrieval models when based on word embeddings compared to when knowledge graph entity embeddings are used? and (iii) is there significant difference between using locally trained neural embeddings compared to when globally trained neural embeddings are used? We examine these three research questions across both hard and all queries. Our study finds that word embeddings do not show competitive performance to any of the baselines. In contrast, entity embeddings show competitive performance to the baselines and when interpolated, outperform the best baselines for both hard and soft queries. 相似文献
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Fattane Zarrinkalam Mohsen Kahani Ebrahim Bagheri 《Information processing & management》2018,54(2):339-357
Inferring users’ interests from their activities on social networks has been an emerging research topic in the recent years. Most existing approaches heavily rely on the explicit contributions (posts) of a user and overlook users’ implicit interests, i.e., those potential user interests that the user did not explicitly mention but might have interest in. Given a set of active topics present in a social network in a specified time interval, our goal is to build an interest profile for a user over these topics by considering both explicit and implicit interests of the user. The reason for this is that the interests of free-riders and cold start users who constitute a large majority of social network users, cannot be directly identified from their explicit contributions to the social network. Specifically, to infer users’ implicit interests, we propose a graph-based link prediction schema that operates over a representation model consisting of three types of information: user explicit contributions to topics, relationships between users, and the relatedness between topics. Through extensive experiments on different variants of our representation model and considering both homogeneous and heterogeneous link prediction, we investigate how topic relatedness and users’ homophily relation impact the quality of inferring users’ implicit interests. Comparison with state-of-the-art baselines on a real-world Twitter dataset demonstrates the effectiveness of our model in inferring users’ interests in terms of perplexity and in the context of retweet prediction application. Moreover, we further show that the impact of our work is especially meaningful when considered in case of free-riders and cold start users. 相似文献
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Neda Dadgar Seyed Ebrahim Alavi Maedeh Koohi Moftakhari Esfahani Azim Akbarzadeh 《Indian journal of clinical biochemistry : IJCB》2013,28(4):410-412
Nano carriers have greatly revolutionized the treatment of most diseases recently. One of these nano carriers, liposomes, has got particular significance. On the other hand, Artemisinin which is used as an effective anticancer drug has some side effects. To reduce such side effects, liposomes can be employed. In order to prepare pegylated nanoliposomal artemisinin, particular proportions of phosphatidylcholine, polyethylene glycol 2000 and artemisinin were combined. As a result, the mean diameter of nano liposomes is 455 nm. Besides, the encapsulation efficiency and the drug release from pegylated nanoliposomes for pegylated nanoliposomal artemisinin are respectively 91.62 ± 3.5 and 5.17 %. The results also show that IC50 of the produced formulation is less than that of the standard drug. This study reveals that the amount of artemisinin cytotoxicity compared to standard drug is increased by pegylated nanoliposomal formulation. 相似文献
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Ebrahim Mohammadpour Mohamed Najib Abdul Ghafar 《Scandinavian Journal of Educational Research》2014,58(2):189-221
Achievement in mathematics of eighth-grade students is modeled as a function of within-school, between-school and cross-country differences. The data were obtained from 217,728 students, within 7,216 secondary schools, in 48 countries, who participated in the 2007 Trends in International Mathematics and Science Study. Multilevel analysis showed that out of the total variance in mathematics achievement, 40.39%, 20.61%, and 38.99% were accounted for within-school, between-school-within-country, and cross-country differences, respectively. Mathematics self-concept followed by socioeconomic status was the strongest predictor of achievement at the student level. At the school level, school location yielded the strongest link to achievement, while at the country level socioeconomic status was the main predictor of national mathematics average. 相似文献