How to Convey Resilience: Towards A Taxonomy for Conversational Agent Breakdown Recovery Strategies

Conversational agents (CAs) have permeated our everyday lives in the past decade. Yet, the CAs we encounter today are far from perfect as they are still prone to breakdowns. Studies have shown that breakdowns have an immense impact on the user-CA relationship, user satisfaction, and retention. Therefore, it is important to investigate how to react and recover from breakdowns appropriately so that failures do not impair the CA experience lastingly. Examples for recovery strategies are the assumption of the most likely user intent (CA self-repair) or to ask for clarification (user-repair). In this paper, we iteratively develop a taxonomy to classify breakdown recovery strategies based on studies from scholarly literature and experiements with productive CA instances, and identify the current best practices described using our taxonomy. We aim to synthesize, structure and further the knowledge on breakdown handling and to provide a common language to describe recovery strategies

A Study of Effective Teaching Strategies in A Kindergarten Chinese Immersion Class

The research question addressed in this capstone is, what teaching methods or strategies are effective in terms of teaching the target language, Chinese, as well as teaching other content areas through the target language for kindergarten students in a Chinese immersion program. The motivating factor for this capstone is the scarcity of existing research about specific teaching methods in this type of schools in the United States. The author looks for the effectiveness of Units of Inquiry learning model by documenting students’ response and reaction for multiple activities or projects. She tries to find out whether such learning model generates a longer lasting memory. She discusses whether the complexity of a Chinese character or a weak corresponding English-Chinese meaning is a challenge for beginner learners. She also addresses the uniqueness of Mathematicrelated language in Chinese and its influence in developing kindergarten students’ number sense

Closing the Gap Between Short and Long XORs for Model Counting

Many recent algorithms for approximate model counting are based on a reduction to combinatorial searches over random subsets of the space defined by parity or XOR constraints. Long parity constraints (involving many variables) provide strong theoretical guarantees but are computationally difficult. Short parity constraints are easier to solve but have weaker statistical properties. It is currently not known how long these parity constraints need to be. We close the gap by providing matching necessary and sufficient conditions on the required asymptotic length of the parity constraints. Further, we provide a new family of lower bounds and the first non-trivial upper bounds on the model count that are valid for arbitrarily short XORs. We empirically demonstrate the effectiveness of these bounds on model counting benchmarks and in a Satisfiability Modulo Theory (SMT) application motivated by the analysis of contingency tables in statistics.Comment: The 30th Association for the Advancement of Artificial Intelligence (AAAI-16) Conferenc

My Virtual Colleague: A State-of-the-Art Analysis of Conversational Agents for the Workplace

Conversational interfaces at the workplace are not a new idea, but it is only the recent technological advancements that turned what was once a vision into near-future reality. Improved reliability and accuracy enable conversational systems to be used in higher stake environments, such as the workplace. In this work, we perform a literature review on concepts proposed to incorporate Conversational Agents (CA) into the workplace. We found 29 workplace CAs designed for workers that contribute to eight different application domains. Based on the studies of these CAs, we compiled a list of aspects to be considered when designing such CAs and identified starting points for further research