Personalized Education; Solving a Group Formation and Scheduling Problem for Educational Content

ABSTRACT Wether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective; (1.) group students so that they can maximally benefit from peer interaction and (2.) find an optimal schedule of the educational material for each group. Thus, in this paper we solve the problem of team formation and content scheduling for education. Given a time frame d, a set of students S with their required need to learn different activities T and given k as the number of desired groups, we study the problem of finding k group of students. The goal is to teach students within time frame d such that their potential for learning is maximized and find the best schedule for each group. We show this problem to be NP-hard and develop a polynomial algorithm for it. We show our algorithm to be effective both on synthetic as well as a real data set. For our experiments we use real data on students' grades in a Computer Science department. As part of our contribution we release a semi-synthetic dataset that mimics the properties of the real data

Team Formation for Scheduling Educational Material in Massive Online Classes

Whether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective, 1 group students so that they can maximally benefit from peer interaction and 2 find an optimal schedule of the educational material for each group. Thus, in this paper, we solve the problem of team formation and content scheduling for education. Given a time frame d, a set of students S with their required need to learn different activities T and given k as the number of desired groups, we study the problem of finding k group of students. The goal is to teach students within time frame d such that their potential for learning is maximized and find the best schedule for each group. We show this problem to be NP-hard and develop a polynomial algorithm for it. We show our algorithm to be effective both on synthetic as well as a real data set. For our experiments, we use real data on students' grades in a Computer Science department. As part of our contribution, we release a semi-synthetic dataset that mimics the properties of the real data

A Qualitative Study of Student-Centered Learning Practices in New England High Schools

In early 2015, the Nellie Mae Education Foundation (NMEF) contracted with the UMass Donahue Institute (UMDI) to conduct a qualitative study examining the implementation of student-centered learning (SCL) practices in select public high schools in New England. This study extends lines of inquiry explored through a prior (2014) project that UMDI conducted for NMEF. The 2014 study employed survey methodology to examine the prevalence of student-centered practices in public high schools across New England. The present study builds upon the investigation, using a variety of qualitative methods to further probe the richness and complexity of SCL approaches in use across the region. Specifically, this study was designed to address what student-centered practices "look like" in an array of contexts. The study also addresses the perceived impacts that SCL approaches have on students, staff, and schools. Additionally, it highlights the broad array of factors within and beyond school walls that reportedly foster and challenge the implementation of SCL practices. This study seeks to help NMEF understand the intricacies of SCL and provides strategic considerations for how Nellie Mae can promote the adoption and development of student-centered practices in the region.Nellie Mae organizes student-centered learning by four tenets: (1) learning is personalized; (2) learning is competency-based; (3) learning takes place anytime, anywhere; and (4) students take ownership.Specifically, the study addresses five research questions:What are the characteristics of student-centered practices in relation to the four SCL tenets? How are SCL approaches implemented?What are the salient contextual factors (e.g., systems, structures, policies, procedures) associated with the implementation of SCL practices? How do they support, impede, and otherwise shape the adoption, development, and implementation of SCL approaches?How are schools with moderate and high levels of SCL implementation organized to foster SCL practices? What mechanisms are in place to promote student-centered learning?What is the role of SCL approaches in schools and classrooms? In what ways, if at all, are they embedded in the goals and practices of schools and classrooms?What is the quality of SCL instructional practices in study schools? What relationships, if any, do administrators and educators perceive between these approaches and student learning

A School of Choice: A Case Study of an Instructional Learning Model in a Public School System

This case study focused on the understandings of the administration and teaching staff with regard to the implementation and student academic growth of the B-L Upward program. The understandings were formed from data collected through structured, face-to-face interviews. The questioning of the staff members assisted in determining an understanding of the instructional model of the B-L Upward program. The experimental nature of the B-L Upward program allowed students, primarily those graduating from eighth grade and heading into high school, to choose an alternative to the traditional secondary learning environment. The current case study is an examination of the B-L Upward program through the interview process involving the administrative and teaching staff with regard to program implementation and student academic growth. Four members of the administrative staff directly responsible for the management of the B-L Upward program and eight members of the teaching staff currently employed at the school were interviewed regarding their understandings of the BLU program. The case study approach provides a detailed picture of the understandings of these staff members. Recommendations for practice and for the continuation of further research were included at the study’s conclusion

On the use of case-based planning for e-learning personalization

This is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications, 60, 1-15, 2016. DOI:10.1016/j.eswa.2016.04.030In this paper we propose myPTutor, a general and effective approach which uses AI planning techniques to create fully tailored learning routes, as sequences of Learning Objects (LOs) that fit the pedagogical and students’ requirements. myPTutor has a potential applicability to support e-learning personalization by producing, and automatically solving, a planning model from (and to) e-learning standards in a vast number of real scenarios, from small to medium/large e-learning communities. Our experiments demonstrate that we can solve scenarios with large courses and a high number of students. Therefore, it is perfectly valid for schools, high schools and universities, especially if they already use Moodle, on top of which we have implemented myPTutor. It is also of practical significance for repairing unexpected discrepancies (while the students are executing their learning routes) by using a Case-Based Planning adaptation process that reduces the differences between the original and the new route, thus enhancing the learning process. © 2016 Elsevier Ltd. All rights reserved.This work has been partially funded by the Consolider AT project CSD2007-0022 INGENIO 2010 of the Spanish Ministry of Science and Innovation, the MICINN project TIN2011-27652-C03-01, the MINECO and FEDER project TIN2014-55637-C2-2-R, the Mexican National Council of Science and Technology, the Valencian Prometeo project II/2013/019 and the BW5053 research project of the Free University of Bozen-Bolzano.Garrido Tejero, A.; Morales, L.; Serina, I. (2016). On the use of case-based planning for e-learning personalization. Expert Systems with Applications. 60:1-15. https://doi.org/10.1016/j.eswa.2016.04.030S1156

Improving School Improvement

PREFACEIn opening this volume, you might be thinking:Is another book on school improvement really needed?Clearly our answer is yes. Our analyses of prevailing school improvement legislation, planning, and literature indicates fundamental deficiencies, especially with respect to enhancing equity of opportunity and closing the achievement gap.Here is what our work uniquely brings to policy and planning tables:(1) An expanded framework for school improvement – We highlight that moving from a two- to a three-component policy and practice framework is essential for closing the opportunity and achievement gaps. (That is, expanding from focusing primarily on instruction and management/government concerns by establishing a third primary component to improve how schools address barriers to learning and teaching.)(2) An emphasis on integrating a deep understanding of motivation – We underscore that concerns about engagement, management of behavior, school climate, equity of opportunity, and student outcomes require an up-to-date grasp of motivation and especially intrinsic motivation.(3) Clarification of the nature and scope of personalized teaching – We define personalization as the process of matching learner motivation and capabilities and stress that it is the learner's perception that determines whether the match is a good one.(4) A reframing of remediation and special education – We formulate these processes as personalized special assistance that is applied in and out of classrooms and practiced in a sequential and hierarchical manner.(5) A prototype for transforming student and learning supports – We provide a framework for a unified, comprehensive, and equitable system designed to address barriers to learning and teaching and re-engage disconnected students and families.(6) A reworking of the leadership structure for whole school improvement --We outline how the operational infrastructure can and must be realigned in keeping with a three component school improvement framework.(7) A systemic approach to enhancing school-community collaboration – We delineate a leadership role for schools in outreaching to communities in order to work on shared concerns through a formal collaborative operational infrastructure that enables weaving together resources to advance the work.(8) An expanded framework for school accountability – We reframe school accountability to ensure a balanced approach that accounts for a shift to a three component school improvement policy.(9) Guidance for substantive, scalable, and sustainable systemic changes –We frame mechanisms and discuss lessons learned related to facilitating fundamental systemic changes and replicating and sustaining them across a district.The frameworks and practices presented are based on our many years of work in schools and from efforts to enhance school-community collaboration. We incorporate insights from various theories and the large body of relevant research and from lessons learned and shared by many school leaders and staff who strive everyday to do their best for children.Our emphasis on new directions in no way is meant to demean current efforts. We know that the demands placed on those working in schools go well beyond what anyone should be asked to do. Given the current working conditions in many schools, our intent is to help make the hard work generate better results. To this end, we highlight new directions and systemic pathways for improving school outcomes.Some of what we propose is difficult to accomplish. Hopefully, the fact that there are schools, districts, and state agencies already trailblazing the way will engender a sense of hope and encouragement to those committed to innovation.It will be obvious that our work owes much to many. We are especially grateful to those who are pioneering major systemic changes across the country. These leaders and so many in the field have generously offered their insights and wisdom. And, of course, we are indebted to hundreds of scholars whose research and writing is a shared treasure. As always, we take this opportunity to thank Perry Nelson and the host of graduate and undergraduate students at UCLA who contribute so much to our work each day, and to the many young people and their families who continue to teach us all.Respectfully submitted for your consideration,Howard Adelman & Linda Taylo

Relationships, Rigor, and Readiness: Strategies for Improving High Schools

This report offers lessons from the last in a series of three high school reform conferences sponsored by MDRC, the Council of the Great City Schools, and the National High School Alliance. This conference in June 2007 brought together leaders from 22 midsize school districts to describe their reform initiatives and to discuss ways in which research and evaluation can inform and complement school change