A Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare

Reinforcement learning (RL) has emerged as a powerful approach for tackling complex medical decision-making problems such as treatment planning, personalized medicine, and optimizing the scheduling of surgeries and appointments. It has gained significant attention in the field of Natural Language Processing (NLP) due to its ability to learn optimal strategies for tasks such as dialogue systems, machine translation, and question-answering. This paper presents a review of the RL techniques in NLP, highlighting key advancements, challenges, and applications in healthcare. The review begins by visualizing a roadmap of machine learning and its applications in healthcare. And then it explores the integration of RL with NLP tasks. We examined dialogue systems where RL enables the learning of conversational strategies, RL-based machine translation models, question-answering systems, text summarization, and information extraction. Additionally, ethical considerations and biases in RL-NLP systems are addressed

Principal And Instructional Coach Partnerships For Instructional Leadership: A Case Study Of Interactions And Teacher Perceptions

This qualitative case study examined conversations and interactions between an intermediate school principal and a team of content specific instructional coaches to investigate the presence of shared instructional leadership and how the interactions and responses of the two actors might support teachers’ professional growth and refinement of instructional practices. An initial interview with the campus principal was used to establish her goals for instructional leadership. Over a six-week period, these goals were tracked through observations and coding of weekly meetings between the principal and coaches and then traced through the coaches’ work with teachers. Findings indicated that the principal was attempting to utilize shared leadership to augment her instructional leadership, but that the results were contingent upon the quality of the leadership team’s internal dynamics as well as the strength of focus on the desired goals. Instructional coaches were utilized by both the principal and the teachers as intermediaries of instructional leadership. One coach maintained a strong goal focus, which teachers perceived as very supportive to their growth, resulting in gains of approximately 30 points for struggling students

Building a New Frame of Reference: An Adult Transformational Approach

Coaching is a process by which a coach engages with a client to help realize personal or professional development goals. A successful coaching process is holistic; taking into account the individual’s expressed desires, their observable behaviors and relationships, all in the context of their needs. Reflecting on how theory informs a coaching practice is important for the practitioner to move beyond intuition and permit theory to influence interventions while also allowing for the observable data to be grounded in a framework that further informs their practice. This paper presents the case study of an OCEC Coaching Practicum Engagement and subsequent work done after the original contract expired. In addition, an exploration of the ethical values ascribed to by the Coach, the theory that informed the methods used during the coaching engagement, and how the data contributed to the Coach’s theoretical view and methods used will be included. In consideration for the importance of self-awareness during the coaching process this paper will be written in the first person, from the perspective of the Coach, and integrate personal background and reflection throughout the stages of the coaching engagement

Making the Value of Development Visible: A Sequential Mixed Methodology Study of the Integral Impact of Post-Classroom Leader and Leadership Development

In a time of increasing complexity, many organizations invest in leadership development programs to prepare those who will assume the role of leader. Although many studies have evaluated programs’ impact, the questions remain: does development happen in leadership development program? If so, what kind of development? And what is the participant’s experience of personal or organizational impact? The purpose of this sequential mixed methodology study is to address these three questions utilizing an online follow-through platform as a lens on 248 participants in the Center for Creative Leadership’s Leadership Development Program (LDP) who reported completing their LDP goals. Those who completed their development goals in the twelve weeks following the LDP face-to-face classroom phase were asked What was the personal or organizational impact of completing this goal? From thematic analysis of the participant’s experience of impact, a taxonomy of 82 content codes emerged; these were then clustered into eight domains of increasing interpersonal space. The codes and domains were utilized to generate frequency counts, revealing first-person accounts of impact that extended beyond the individual into interpersonal, team, and organizational domains; the reports of impact included both interior (subjective worldview and shared culture) and exterior (observable behavior, performance, structure, systems, and processes) realms highlighting the impact on individuals and collectives. Codes surfaced evidence of both horizontal and vertical development, with seven emergent hypotheses being investigated for their role in predicting inclusion in the vertical development codes. This research integrates the literature in various domains to discuss findings: leader development, leadership development, leadership development program design, postclassroom development, adult development, horizontal development, vertical development, integral theory, hierarchical complexity, and online follow-through technology. This study helps make visible the value of development in times of increasing complexity, adaptive challenges, and a diverse workforce; development builds an ability for individuals and collectives to catalyze new insights from reasoning that is more complex. The electronic version of this dissertation is accessible at the OhioLINK ETD Center, https://etd.ohiolink.ed

Software-based dialogue systems: Survey, taxonomy and challenges

The use of natural language interfaces in the field of human-computer interaction is undergoing intense study through dedicated scientific and industrial research. The latest contributions in the field, including deep learning approaches like recurrent neural networks, the potential of context-aware strategies and user-centred design approaches, have brought back the attention of the community to software-based dialogue systems, generally known as conversational agents or chatbots. Nonetheless, and given the novelty of the field, a generic, context-independent overview on the current state of research of conversational agents covering all research perspectives involved is missing. Motivated by this context, this paper reports a survey of the current state of research of conversational agents through a systematic literature review of secondary studies. The conducted research is designed to develop an exhaustive perspective through a clear presentation of the aggregated knowledge published by recent literature within a variety of domains, research focuses and contexts. As a result, this research proposes a holistic taxonomy of the different dimensions involved in the conversational agents’ field, which is expected to help researchers and to lay the groundwork for future research in the field of natural language interfaces.With the support from the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund. The corresponding author gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the inancial support of his predoctoral grant FPI-UPC. This paper has been funded by the Spanish Ministerio de Ciencia e Innovación under project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033.Peer ReviewedPostprint (author's final draft

Ubiquitous Technologies for Emotion Recognition

Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevance to understand human behavior and its consequences. Despite the great efforts made in the past in the study of human emotions, it is only now, with the advent of wearable, mobile, and ubiquitous technologies, that we can aim to sense and recognize emotions, continuously and in real time. This book brings together the latest experiences, findings, and developments regarding ubiquitous sensing, modeling, and the recognition of human emotions