PEER AND STUDENT-FACULTY RELATIONS IN COMMUNITY COLLEGES

This study investigated differences in peer and student?faculty relationships of male and female community college students. Men reported more frequent participation in college activities, whereas women reported more frequent involvement in less formal activities such as studying with other students. Women had less difficulty than men meeting and making friends. For both men and women, little student?faculty interaction outside the classroom was reported.     

Academic and Student Affairs Issues Post Hurricane Katrina

This article describes several issues in the academic and student affairs areas faced by students and faculty in the post-Katrina destruction environment. Cases are used to illustrate the issues, and a call is made for increased disaster readiness plans.     

Gender and Ethnicity Among Community College Students: The Relationship Between Adlerian Themes

This study explored the relationship between Adlerian themes, gender, and ethnicity. Results indicate significant differences between Hispanic and Caucasian (non-Hispanic) community college students in Belonging and Social Interest as measured by the BASIS-A. Differences between males and females in Going Along and Wanting Recognition are also explored. The findings are discussed in relation to college students, teaching, and classroom climates.     

COMMUNITY SERVICES: COMMUNITY COLLEGE FACULTY PERCEPTIONS AND PARTICIPATION

This study determined full‐time faculty members’ perceptions of and involvement in community services at community colleges in Ohio. A total of 249 full‐time faculty responded to the survey instrument representing 83.0% of the total sample. Data were analyzed by either the t test or the one‐way analysis of variance and Scheffe's post hoc analysis.

Results showed that involvement in planning and teaching within community services seem to be a key factor relative to how full‐time faculty perceive community services activities. Moreover, certain personal and professional characteristics of full‐time faculty members seem to influence their attitudes toward and their involvement in community services.     

Promoting a participatory convergence in a Spanish context: an inter-university action research project using visual narrative

ABSTRACT

This article focuses on the deconstruction of an inter-university action research project that has allowed us to rethink our teaching and research, questioning the social, political and ethical dimensions of the university. Following the pre-assembly proposal to promote participatory convergence, organized within the framework of the 1^st Global Assembly for Knowledge Democracy (2017), an action research process was implemented in order to generate systematic inquiry around the current situation of the university and the need to act and rethink our commitment to promoting changes in this context. We have reflected on the meaning of democratization, rethinking the pedagogical relationship with our students and how we critically commit them to promote activism. We generated an environment where we look for the meaning of our practices by means of a visual narrative which has enabled us to weave and identify our own biography and become aware of where we are and why we act in one way or another. We have also focused on the search for the meaning of our actions in relation to the community we belong to and how to deal with the challenges of social justice, encouraging collaboration with other networks in a wider inter-university framework.     

Making Plans for Michael: providing for a student with moderate learning difficulties in a secondary academy

The profile of a student with learning difficulties is described and also the learning context in 2017. Previous models of provision are then described in terms of their aetiology with discussion of strengths and shortcomings. Some influential features of curriculum planning and delivery are identified. A model of provision involving specific literacy teaching and differentiation is advocated.     

Revisiting the cluster-based paradigm for implicit search result diversification

To cope with ambiguous and/or underspecified queries, search result diversification (SRD) is a key technique that has attracted a lot of attention. This paper focuses on implicit SRD, where the subtopics underlying a query are unknown. Many existing methods appeal to the greedy strategy for generating diversified results. A common practice is using a heuristic criterion for making the locally optimal choice at each round. As a result, it is difficult to know whether the failures are caused by the optimization criterion or the setting of parameters. Different from previous studies, we formulate implicit SRD as a process of selecting and ranking k exemplar documents through integer linear programming (ILP). The key idea is that: for a specific query, we expect to maximize the overall relevance of the k exemplar documents. Meanwhile, we wish to maximize the representativeness of the selected exemplar documents with respect to the non-selected documents. Intuitively, if the selected exemplar documents concisely represent the entire set of documents, the novelty and diversity will naturally arise. Moreover, we propose two approaches ILP4ID (Integer Linear Programming for Implicit SRD) and AP4ID (Affinity Propagation for Implicit SRD) for solving the proposed formulation of implicit SRD. In particular, ILP4ID appeals to the strategy of bound-and-branch and is able to obtain the optimal solution. AP4ID being an approximate method transforms the target problem as a maximum-a-posteriori inference problem, and the message passing algorithm is adopted to find the solution. Furthermore, we investigate the differences and connections between the proposed models and prior models by casting them as different variants of the cluster-based paradigm for implicit SRD. To validate the effectiveness and efficiency of the proposed approaches, we conduct a series of experiments on four benchmark TREC diversity collections. The experimental results demonstrate that: (1) The proposed methods, especially ILP4ID, can achieve substantially improved performance over the state-of-the-art unsupervised methods for implicit SRD. (2) The initial runs, the number of input documents, query types, the ways of computing document similarity, the pre-defined cluster number and the optimization algorithm significantly affect the performance of diversification models. Careful examinations of these factors are highly recommended in the development of implicit SRD methods. Based on the in-depth study of different types of methods for implicit SRD, we provide additional insight into the cluster-based paradigm for implicit SRD. In particular, how the methods relying on greedy strategies impact the performance of implicit SRD, and how a particular diversification model should be fine-tuned.