Quality Assessment for E-learning: a Benchmarking Approach (Third edition)

The primary purpose of this manual is to provide a set of benchmarks, quality criteria and notes for guidance against which e-learning programmes and their support systems may be judged. The manual should therefore be seen primarily as a reference tool for the assessment or review of e-learning programmes and the systems which support them. However, the manual should also prove to be useful to staff in institutions concerned with the design, development, teaching, assessment and support of e-learning programmes. It is hoped that course developers, teachers and other stakeholders will see the manual as a useful development and/or improvement tool for incorporation in their own institutional systems of monitoring, evaluation and enhancement

Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences

This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering

Machine Education: Designing semantically ordered and ontologically guided modular neural networks

The literature on machine teaching, machine education, and curriculum design for machines is in its infancy with sparse papers on the topic primarily focusing on data and model engineering factors to improve machine learning. In this paper, we first discuss selected attempts to date on machine teaching and education. We then bring theories and methodologies together from human education to structure and mathematically define the core problems in lesson design for machine education and the modelling approaches required to support the steps for machine education. Last, but not least, we offer an ontology-based methodology to guide the development of lesson plans to produce transparent and explainable modular learning machines, including neural networks.Comment: IEEE Symposium Series on Computational Intelligence, 201

Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning

The realities of the 21st-century learner require that schools and educators fundamentally change their practice. "Educators must produce college- and career-ready graduates that reflect the future these students will face. And, they must facilitate learning through means that align with the defining attributes of this generation of learners."Today, we know more than ever about how students learn, acknowledging that the process isn't the same for every student and doesn't remain the same for each individual, depending upon maturation and the content being learned. We know that students want to progress at a pace that allows them to master new concepts and skills, to access a variety of resources, to receive timely feedback on their progress, to demonstrate their knowledge in multiple ways and to get direction, support and feedback from—as well as collaborate with—experts, teachers, tutors and other students.The result is a growing demand for student-centered, transformative digital learning using competency education as an underpinning.iNACOL released this paper to illustrate the technical requirements and functionalities that learning management systems need to shift toward student-centered instructional models. This comprehensive framework will help districts and schools determine what systems to use and integrate as they being their journey toward student-centered learning, as well as how systems integration aligns with their organizational vision, educational goals and strategic plans.Educators can use this report to optimize student learning and promote innovation in their own student-centered learning environments. The report will help school leaders understand the complex technologies needed to optimize personalized learning and how to use data and analytics to improve practices, and can assist technology leaders in re-engineering systems to support the key nuances of student-centered learning

Digitalization and Innovation

Developments in digital technology offer new opportunities to design new products and services. However, creating such digitalized products and services often creates new problems and challenges to firms that are trying to innovate. In this essay, we analyze the impact of digitalization of products and services on innovations. In particular, we argue that digitalization of products will lead to an emergence of new layered product architecture. The layered architecture is characterized by its generative design rules that connect loosely coupled heterogeneous layers. It is pregnant with the potential of unbounded innovations. The new product architecture will require organizations to adopt a new organizing logic of innovation that we dubbed as doubly distributed innovation network. Based on this analysis, we propose five key issues that future researchers need to explore.innovation, innovation, product architecture, design rules

Applications of additive manufacturing in the construction industry

Additive Manufacturing (AM) or 3D printing, the process of fabricating components in a layer-wise fashion, has been increasingly applied in industries such as automotives and aerospace. In the 1990s, interest from the construction industry evolved through several experimental applications looking to reduce labor cost, waste material, or create complex shapes that are difficult to build using conventional construction methods. However, the full range of potential applications for construction have not been explored, and the industry’s involvement with AM is still considered at its early stages. As a first step, this thesis provides an extensive literature review of AM as it relates to the construction industry. This research identifies the most significant AM processes, compared to subtractive or formative processes, as well as some technologies and materials being used. A recommendation is given for potential advancements in applications for construction. The thesis also explores the use of typical small-scale material extrusion desktop 3D printers to print and test customized fastener-free connections. The intent of these connection tests is to explore novel ways in which AM technology can be used for structural and non-structural applications using commercial polymers. The connections were inspired by traditional wood joinery and modern proprietary connections. A four-point bending test was used to evaluate their potential structural performance in bending and to identify connection types that could be used for future investigations. Before AM can realize its full potential, interdisciplinary research is still needed to provide new materials, reliable printed parts, and new and repeatable processes. This thesis provides initial steps toward this goal by finding research gaps, identifying research trends in the area, and by exploring initial benefits and limitations for non-structural and structural applications in construction using available small-scale AM technology.Civil, Architectural, and Environmental Engineerin

Corpora and evaluation tools for multilingual named entity grammar development

We present an effort for the development of multilingual named entity grammars in a unification-based finite-state formalism (SProUT). Following an extended version of the MUC7 standard, we have developed Named Entity Recognition grammars for German, Chinese, Japanese, French, Spanish, English, and Czech. The grammars recognize person names, organizations, geographical locations, currency, time and date expressions. Subgrammars and gazetteers are shared as much as possible for the grammars of the different languages. Multilingual corpora from the business domain are used for grammar development and evaluation. The annotation format (named entity and other linguistic information) is described. We present an evaluation tool which provides detailed statistics and diagnostics, allows for partial matching of annotations, and supports user-defined mappings between different annotation and grammar output formats