Competency Implications of Changing Human Resource Roles

[Excerpt] The present study examines which competencies will be necessary to perform key human resource roles over the next decade at Eastman Kodak Company. This project was a critical component of an ongoing quality process to improve organizational capability. The results establish a platform that will enable Kodak to better assess, plan, develop, and measure the capability of human resource staff

Decision Sheet and Learning Diary: New Tools for Improved Learning Through the Case Method

Of the three phases of learning through the case method, instructors have focused on the in-class phase in training of both teachers and participants. The other two phases, pre-class preparation and post class-reflection, have not received much attention leading to lack of exploitation of the full learning potential from the method. This paper shares continued efforts to conceptualize and develop two tools, decision sheet and learning diary, to strengthen the two phases. These were designed and tested in three executive development programmes. The results and our reflections suggest that the tools enhance the process of learning and the learning itself.

Creating, Doing, and Sustaining OER: Lessons from Six Open Educational Resource Projects

The development of free-to-use open educational resources (OER) has generated a dynamic field of widespread interest and study regarding methods for creating and sustaining OER. To help foster a thriving OER movement with potential for knowledge-sharing across program, organizational and national boundaries, the Institute for Knowledge Management in Education (ISKME), developed and conducted case study research programs in collaboration with six OER projects from around the world. Embodying a range of challenges and opportunities among a diverse set of OER projects, the case studies intended to track, analyze and share key developments in the creation, use and reuse of OER. The specific cases include: CurriculumNet, Curriki, Free High School Science Texts (FHSST), Training Commons, Stanford Encyclopedia of Philosophy (SEP), and Teachers' Domain

Efficient Deep Reinforcement Learning via Adaptive Policy Transfer

Transfer Learning (TL) has shown great potential to accelerate Reinforcement Learning (RL) by leveraging prior knowledge from past learned policies of relevant tasks. Existing transfer approaches either explicitly computes the similarity between tasks or select appropriate source policies to provide guided explorations for the target task. However, how to directly optimize the target policy by alternatively utilizing knowledge from appropriate source policies without explicitly measuring the similarity is currently missing. In this paper, we propose a novel Policy Transfer Framework (PTF) to accelerate RL by taking advantage of this idea. Our framework learns when and which source policy is the best to reuse for the target policy and when to terminate it by modeling multi-policy transfer as the option learning problem. PTF can be easily combined with existing deep RL approaches. Experimental results show it significantly accelerates the learning process and surpasses state-of-the-art policy transfer methods in terms of learning efficiency and final performance in both discrete and continuous action spaces.Comment: Accepted by IJCAI'202

Applying Service Design Methods for Improving Communication and Collaboration of Internal Stakeholders in a Growing IT Organization

Service design is known for various methods that are facilitating healthy communication and collaboration with customers however it seems to be difficult to find studies that analyze service design methods improving communication and collaboration within the organization. Therefore, service design methods were applied from a new perspective. The goal of this thesis was to investigate how to improve communication and collaboration of internal stakeholders in a growing IT organization. Action research was used as the research method in this thesis work. The literature review was conducted to identify suitable services design methods for the empirical study. As a result of the literature review, service blueprint and participatory methods were selected. The empirical study was based on both qualitative and quantitative data collection techniques, such as 36 interviews, a workshop, observations and a survey. The empirical study revealed that the scope of service blueprint had to be modified to support communication and collaboration between internal stakeholders. Changes mostly affected physical size and accuracy level of the visualization. The participatory workshop was found to be effective for collaboration support. Furthermore more valuable results would be achieved if workshop arrangements and engagement activities were aligned with the workshop participants. Service blueprint and participatory methods were found to positively affect communication and collaboration of internal stakeholder in a growing IT organization. These service design methods provided a big picture of the service delivery process. Also visibility on the processes increased common understanding and eased internal communication in an organization. Furthermore, a healthy communication and collaboration environment was managed. This environment allowed sharing experiences and deciding on improvements regarding organizational processes. The results of the study indicate that the service blueprint and participatory methods can provide deep understanding of the service delivery process across the organization and support improvement of organizational processes. The findings of this thesis suggest the way service design methods can be applied to improve communication and collaboration of internal stakeholders in a growing IT organization

Managing for Learning and Impact

Over the past three years, the King Baudouin Foundation has developed a more systematic approach for the evaluation of its projects, which FSG helped codify in the KBF Project Management Guide: 'Managing for Learning and Impact'. There is a growing interest of foundations in Europe to evaluate the intended impact of their projects and programs. Foundations invest in an impact-driven philanthropy and therefore develop specific strategies, activities and tools

DAC: The Double Actor-Critic Architecture for Learning Options

We reformulate the option framework as two parallel augmented MDPs. Under this novel formulation, all policy optimization algorithms can be used off the shelf to learn intra-option policies, option termination conditions, and a master policy over options. We apply an actor-critic algorithm on each augmented MDP, yielding the Double Actor-Critic (DAC) architecture. Furthermore, we show that, when state-value functions are used as critics, one critic can be expressed in terms of the other, and hence only one critic is necessary. We conduct an empirical study on challenging robot simulation tasks. In a transfer learning setting, DAC outperforms both its hierarchy-free counterpart and previous gradient-based option learning algorithms.Comment: NeurIPS 201