The busyness of everyday life means that those with casual interest in additional learning opportunities are often unable to schedule regular time and effort for studying. In this paper, we explore how to augment information technologies that people use on a daily basis to create micro-learning opportunities. In particular, we examine how a person's existing Web browsing experience-with first language Web pages-can be augmented to teach them second language vocabulary. We present a prototype, ALOE, which runs inside the Firefox Web browser and dynamically augments Web pages by replacing a selected set of English words with their foreign translations. The foreign translations are embedded in the rich context of a Web page's existing English text to promote incidental learning and guessing from context of the translated words. Through a two month user evaluation of ALOE, we found that most participants were able to learn an average of 50 new French vocabulary words.

Many people read online reviews written by other users to learn more about a product or venue. However, the overwhelming amount of user-generated reviews and variance in length, detail and quality across the reviews make it difficult to glean useful information. In this paper, we present the iterative design of our system, called Review Spotlight. It provides a brief overview of reviews using adjective-noun word pairs, and allows the user to quickly explore the reviews in greater detail. Through a laboratory user study which required participants to perform decision making tasks, we showed that participants could form detailed impressions about restaurants and decide between two options significantly faster with Review Spotlight than with traditional review webpages.

Many people read online reviews written by other users to learn more about a product or venue. However, the overwhelming amount of user-generated reviews and variance in length, detail and quality across the reviews make it difficult to glean useful information. In this paper, we present a summarization system called Review Spotlight. It provides a brief overview of reviews by using adjective-noun word pairs extracted from the review text. The system also allows the user to click any word pair to read the original sentences from which the word pair was extracted. We present our system implementation as a Google Chrome browser extension, and an evaluation on how two word pair scoring methods (TF and TF-IDF) affect the identification of useful word pairs. 1