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This study aims to explore postdoctoral scholars’ experiences and perceptions of a teaching certificate program and identify how they use the knowledge and skills developed through the certificate program to improve their teaching practices.

In this case study, the authors explored postdoctoral scholars’ experiences and perceptions of a teaching certificate using a multiple methods and data sources including documents, course evaluations, interviews and surveys.

The teaching certificate program helped postdocs learn the language and theory of teaching and learning in post-secondary education; practice specific strategies and develop confidence in how to teach; network with colleagues about teaching and learning; develop a reflective teaching practice; and contribute to the scholarship of teaching and learning.

The findings from this study will inform efforts to develop new or refine existing approaches to promote teaching and learning professional development opportunities for postdoctoral scholars.

This paper fulfills an identified need to study teaching and learning development for postdoctoral scholars.

Summarization of an entire web site with diverse content may lead to a summary heavily biased towards the site's dominant topics. The purpose of this paper is to present a novel topic‐based framework to address this problem.

A two‐stage framework is proposed. The first stage identifies the main topics covered in a web site via clustering and the second stage summarizes each topic separately. The proposed system is evaluated by a user study and compared with the single‐topic summarization approach.

The user study demonstrates that the clustering‐summarization approach statistically significantly outperforms the plain summarization approach in the multi‐topic web site summarization task. Text‐based clustering based on selecting features with high variance over web pages is reliable; outgoing links are useful if a rich set of cross links is available.

More sophisticated clustering methods than those used in this study are worth investigating. The proposed method should be tested on web content that is less structured than organizational web sites, for example blogs.

The proposed summarization framework can be applied to the effective organization of search engine results and faceted or topical browsing of large web sites.

Several key components are integrated for web site summarization for the first time, including feature selection and link analysis, key phrase and key sentence extraction. Insight into the contributions of links and content to topic‐based summarization was gained. A classification approach is used to minimize the number of parameters.