Teaching peer review reflective processes in accounting

A well designed peer review process in higher education subjects can lead to more confident and reflective learners who become skilled at making independent judgements of their own and others’ work; essential requirements for successful lifelong learning. The challenge for educators is to ensure their students gain these important graduate attributes within the constraints of a range of internal and external tensions currently facing higher education systems, including, respectively, the realities of large undergraduate Accounting subjects, culturally diverse and time-poor academics and students, and increased calls for public accountability of the Higher Education sector by groups such as the OECD. Innovative curriculum and assessment design and collaborative technologies have the capacity to simultaneously provide some measure of relief from these internal and external tensions and to position students as responsible partners in their own learning. This chapter reports on a two phase implementation of an online peer review process as part of the assessment in a large, under-graduate, International Accounting class. Phase One did not include explicit reflective strategies within the process, and anonymous and voluntary student views served to clearly highlight that students were ‘confused’ and ‘hesitant’ about moving away from their own ideas; often mistrusting the conflicting advice received from multiple peer reviewers. A significant number of students also felt that they did not have the skills to constructively review the work of their peers. Phase Two consequently utilised the combined power of e-Technology, peer review feedback and carefully scaffolded and supported reflective practices from Ryan and Ryan’s Teaching and Assessing Reflective Learning (TARL) model (see Chap. 2). Students found the reflective skills support workshop introduced in Phase Two to be highly useful in maximising the benefits of the peer review process, with 83 % reporting it supported them in writing peer reviews, while 90 % of the respondents reporting the workshop supported them in utilising peer and staff feedback.

Teacher peer support in social network sites

This paper describes the types of support that teachers are accessing through the Social Network Site (SNS) 'Facebook'. It describes six ways in which teachers support one another within online groups. It presents evidence from a study of a large, open group of teachers online over a twelve week period, repeated with multiple groups a year later over a one week period. The findings suggest that large open groups in SNSs can be a useful source of pragmatic advice for teachers but that these groups are rarely a place for reflection on or feedback about teaching practice.

Peer to peer English/Chinese cross-language information retrieval

Peer to peer systems have been widely used in the internet. However, most of the peer to peer information systems are still missing some of the important features, for example cross-language IR (Information Retrieval) and collection selection / fusion features. Cross-language IR is the state-of-art research area in IR research community. It has not been used in any real world IR systems yet. Cross-language IR has the ability to issue a query in one language and receive documents in other languages. In typical peer to peer environment, users are from multiple countries. Their collections are definitely in multiple languages. Cross-language IR can help users to find documents more easily. E.g. many Chinese researchers will search research papers in both Chinese and English. With Cross-language IR, they can do one query in Chinese and get documents in two languages. The Out Of Vocabulary (OOV) problem is one of the key research areas in crosslanguage information retrieval. In recent years, web mining was shown to be one of the effective approaches to solving this problem. However, how to extract Multiword Lexical Units (MLUs) from the web content and how to select the correct translations from the extracted candidate MLUs are still two difficult problems in web mining based automated translation approaches. Discovering resource descriptions and merging results obtained from remote search engines are two key issues in distributed information retrieval studies. In uncooperative environments, query-based sampling and normalized-score based merging strategies are well-known approaches to solve such problems. However, such approaches only consider the content of the remote database but do not consider the retrieval performance of the remote search engine. This thesis presents research on building a peer to peer IR system with crosslanguage IR and advance collection profiling technique for fusion features. Particularly, this thesis first presents a new Chinese term measurement and new Chinese MLU extraction process that works well on small corpora. An approach to selection of MLUs in a more accurate manner is also presented. After that, this thesis proposes a collection profiling strategy which can discover not only collection content but also retrieval performance of the remote search engine. Based on collection profiling, a web-based query classification method and two collection fusion approaches are developed and presented in this thesis. Our experiments show that the proposed strategies are effective in merging results in uncooperative peer to peer environments. Here, an uncooperative environment is defined as each peer in the system is autonomous. Peer like to share documents but they do not share collection statistics. This environment is a typical peer to peer IR environment. Finally, all those approaches are grouped together to build up a secure peer to peer multilingual IR system that cooperates through X.509 and email system.