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The purpose of this paper is to present an algorithm to generate story problems via controlled parameters in the domain of mathematics. The generation process is performed in the problem generation module in the context of an intelligent tutoring system suggested in this paper. Controlling the question parameters allows for adapting the generated questions according to the specific student needs. Story problems are selected since they are one of the most important types of problems in mathematics, as they help train students to apply their knowledge to real-world problems. Such problems target improving different student’s skills including literacy skills through reading the problem, recognizing the embedded mathematical information, and applying the required arithmetic operators.

Natural language generation (NLG) techniques are used to control the difficulty level of the generated story problem header in addition to effecting variations from the natural language point of view. The proposed NLG technique is based on different separated knowledge categories to provide flexibility in the generation process and allow porting the module to other contexts, domains, and to other natural languages without a complete redesign.

The approach has been empirically evaluated, and the results show that the generated problems are sound, clear, and naturally readable. This is in addition to the usability of the tutoring system itself.

The generation technique is confined to the problem described using rhetorical schemas. Nevertheless, it can generate any problem provided that the rhetorical schema is available.

Most story problems generation systems limit the variation of the story problems to formulating the sentences that describe the story problem and the associated mathematical operations. In contrast, this paper presents a story problems generation technique that allows variations in the structure of the narrative story as well as the context, sentences, wordings, and mathematical operations. This variability allows assessing different student skills along different dimensions with gradually increasing difficulty levels.

The purpose of this paper is to investigate an efficient means of estimating the ability of students solving problems in the computer-based learning environment.

Item response theory (IRT) and TrueSkill were applied to simulated and real problem solving data to estimate the ability of students solving homework problems in the massive open online course (MOOC). Based on the estimated ability, data mining models predicting whether students can correctly solve homework and quiz problems in the MOOC were developed. The predictive power of IRT- and TrueSkill-based data mining models was compared in terms of Area Under the receiver operating characteristic Curve.

The correlation between students’ ability estimated from IRT and TrueSkill was strong. In addition, IRT- and TrueSkill-based data mining models showed a comparable predictive power when the data included a large number of students. While IRT failed to estimate students’ ability and could not predict their problem solving performance when the data included a small number of students, TrueSkill did not experience such problems.

Estimating students’ ability is critical to determine the most appropriate time for providing instructional scaffolding in the computer-based learning environment. The findings of this study suggest that TrueSkill can be an efficient means for estimating the ability of students solving problems in the computer-based learning environment regardless of the number of students.

This chapter reviews research on math disabilities (MD) from two different points of view: Italian and American. Our goal is to gain consensus on identifying the cognitive deficits that underlie problems associated with MD as well as to provide an overview of some of the instructional approaches to remediate these deficits. The review outlines similarities and differences in the research perspectives between the two countries. Although the results show some consensus on the identification of MD and the cognitive mechanisms associated with this deficit (e.g., working memory), some differences remain between the two research perspectives (e.g., incidence of MD).

Attention has been increasingly devoted to the development of methods for assessing the quality of care in long‐term care (LTC) facilities, especially for government surveillance. A study is described which used the tracer method to provide data on the quality of care in Israeli LTC institutions. Advantages of the tracer method include its incorporation of structural, process and outcome measures and its focus on a number of representative tracer conditions. The study tested the ability of the tracer method to provide data on the quality of care, and facilitated adoption of this methodology by the government for their annual inspections.

While problem and decision analysis has attracted considerable interest in general management fields, it is not a topic commonly found in the marketing management literature. Problem understanding and definition determine management action, and therefore deserve greater attention. Addresses the key issues in marketing management problem analysis by showing why problem definition is important; outlining the nature of marketing problems and the difficulties involved in addressing them; and providing guidelines for management and research practitioners. A diagrammatic review of several problem and decision models provides a broad view of the complex processes involved. One critical factor which comes to the fore in the discussion is the necessity for decision makers and analysts to collaborate, and several techniques for such co‐operation are presented.

The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners’ computational thinking.

By analyzing the mechanism of action of ITF on the development of computational thinking, an ITF strategy and corresponding ITS acting on the whole process of programming problem-solving were developed to realize the evaluation of programming problem-solving ideas based on program logic. On the one hand, a lexical and syntactic analysis of the programming problem solutions input by the learners is performed and presented with a tree-like structure. On the other hand, by comparing multiple algorithms, it is implemented to compare the programming problem solutions entered by the learners with the answers and analyze the gaps to give them back to the learners to promote the improvement of their computational thinking.

This study clarifies the mechanism of the role of ITF-based ITS in the computational thinking development process. Results indicated that the ITS designed in this study is effective in promoting students’ computational thinking, especially for low-level learners. It also helped to improve students’ learning motivation, and reducing cognitive load, while there’s no significant difference among learners of different levels.

This study developed an ITS based on ITF to address the problem of learners’ difficulty in obtaining real-time guidance in the current programming problem-solving-based computational thinking development, providing a good aid for college students’ independent programming learning.

IN July we sugggested that one outcome of the formation of a European Work Study organisation could be a standard certificate of competence, recognised by all the participating countries. That opinion is confirmed after reading carefully through the various memoranda compiled for the conference by representatives. They showed a wide variance in training methods and in the subjects regarded as important.

Introduction Consider a hi‐fi loudspeaker manufacturing company acquired on the brink of insolvency by an American multinational. The new owners discover with growing concern that the product range is obsolete, that manufacturing facilities are totally inadequate and that there is a complete absence of any real management substance or structure. They decide on the need to relocate urgently so as to provide continuity of supply at the very high — a market about to shrink at a rate unprecedented in its history.

This study aims at redefining bounded rationality on the basis of a more socialized view of the individual. In doing so, it introduces “inquisitiveness” as a key disposition that some team members use to assemble and integrate knowledge when solving problems.

Using an agent-based computational simulation, this research models different simulated employees working together in “ad hoc” teams to solve problems.

Results show that inquisitiveness may work as an efficiency “driver” that, when present, economizes on the knowledge needed by team members to solve problems. In addition to that, results also show that environments with many problems are more suitable for inquisitive individuals to be effective.

Following the late Herbert Simon, the paper takes the stance that rationality should be redefined as a socially oriented process and introduces inquisitiveness as one – although probably not the only one – of the characteristics that help individuals and teams to make rational decisions.

Current government policy aims to tackle youth anti-social behaviour and its psychological and social impacts. Given an increased likelihood that young victims of crime are also likely to engage in aggressive or deviant behaviour and to have psychological and social difficulties, interventions are needed which access vulnerable youth with adverse lifestyles to increase well-being and reduce offending. The current project utilised a hospital emergency department (ED) as an appropriate location to identify and interact with youth victims of violent crime; to support key lifestyle risk and mental health difficulties; and build resilience. The purpose of this paper is to use a youth work paradigm, to target vulnerable youth in a health setting at a crisis point where intervention may have a higher chance of uptake.

The study applied a quasi-experimental, longitudinal design. Using the strengths and difficulties questionnaire and the “What Do You Think” component of the ASSET risk assessment, data were collected from 120 youth aged 12-20, at baseline with 66 youth who successfully completed the programme with assessments at baseline and follow-up, at an average of 14 weeks.

There was significant reduction in both psychological problems and lifestyle risk at follow-up.

These findings support the government initiative to intervene in youth violence in healthcare settings. Challenges revolve around increasing participation and greater formalisation of the intervention.

The youth work led violence intervention in the ED is successfully tackling psychological problems and lifestyle risk following injury.