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While deficits for students with learning disabilities (LD) are prevalent in almost all aspects of mathematics, difficulty in the application and understanding of problem-solving tasks are much more challenging to remediate than computational and procedural skills. Given the complexities involved in authentic problem-solving activities emphasized in current mathematics standards and the inherent challenges presented to students with LD, the importance of using strategies and techniques guided by evidence-based practices is paramount. Yet, ineffective instructional strategies for problem solving are still widespread in both mathematics curricula and available teacher resources. In this chapter, we provide a description of a commonly used ineffective problem-solving strategy (i.e., the keyword strategy), an overview of the keyword research, and an explanation for its ineffectiveness. We conclude with a description of three evidenced-based problem-solving approaches and practices that significantly improve the mathematical performance of students with LD.

The purpose of this paper is to explore the possible consequences of the intra-individual level-based perceptions of participative, supportive and instrumental leadership styles and the dissonance factors of leadership styles perceptions on employee engagement using the information-processing and connectionist perspectives of leadership perceptions.

Hypotheses relating to direct and moderated effects of perceptions of leadership styles on employee engagement were tested using a two-stage intra-individual level study (n=172 in each stage). Hierarchical regression analysis was used to test the hypotheses.

The findings revealed that perceptions of preferred and experienced supportive leadership styles are individually important predictors of employee engagement. It was also revealed that differentiated leadership styles have stronger (complementary) effect on employee engagement when the perceptions of experienced participative and supportive leadership styles were aligned with perceptions of respective preferred leadership styles. Furthermore, it was also found that the low level compared to the high level of dissonance factor or the difference between preferred and experienced instrumental leadership style acted as a complementer on employee engagement.

This study has made contributions to facilitate scholars to build better information-processing models and implicit theories for differentiated leadership and employee engagement links. Finally, the study provides new information on the consequence of perceptions of leadership style and the dissonance factor of leadership perceptions on followers’ actions such as employee engagement.

This will be the first empirical study examining the relationships between the dissonance factor of leadership perceptions of participative, supportive and instrumental styles and employee engagement.

As traditional paper manuals and step-by-step instructions have shown to discourage new product learning because of a lack of exploration, the purpose of this paper is to investigate consumer learning from an online and andragogical, that is, adult learning, perspective by identifying relevant consumer e-learning processes in new product learning.

This paper uses thematic and trace analyses on a multi-method data collection, that is, extant e-learning courses, in-depth interviews and non-participant observations.

Emerging findings give light on customized, interactive and iterative e-learning processes depending on consumers’ previous experiences, their learning orientation as adult learners and the characteristics of the online environment. Results provide evidence for the existence of three learning strategies and show how the online environment comes shifting traditional consumer learning paradigms.

This paper contributes to the literature on consumer behavior on two levels. First, the findings highlight the importance of taking an andragogical standpoint to provide a more nuanced and realistic view on consumers’ learning processes in new product learning. Second, the results show how the exploration and interactivity provided by the online environment present beneficial prerequisites for effective consumer learning. More than just being an alternative, online learning is complementary to offline modes of learning to improve consumers’ overall learning experience.

This paper aims to review the notion of schemata in consumer behavior, placing particular emphasis on the conceptualization of brand knowledge, and illustrate how schema theory may act as a unifying conceptual framework to study what consumers know about products and brands. Extant research on how consumers conceptualize brands lacks a single, coherent theoretical framework. The literature is fragmented into different approaches that may prevent comparisons across studies and make it difficult to draw conclusive results.

The paper discusses the central tenets of schema theory and then presents the structure of schematic knowledge and the main typology of consumer schemata. It focuses on the brand schema, delineating its internal properties and drawing analogies with other approaches used to describe consumers’ mental representation of brands.

Schema theory can provide a comprehensive framework to analyze how consumers perceive brand information. A cognitive schema specifies the parameters of knowledge content, discriminates between different types of information and indicates how various pieces of information relate to one another. Importantly, the internal structure of schemata remains stable across conceptual domains, allowing to investigate brand-specific knowledge in different contexts and in conjunction with superordinate and subordinate knowledge structures.

This is the first systematic review of the notion of schemata in consumer behavior. It thoroughly describes how schema theory from psychology has been applied in marketing research to describe the organization of market knowledge and illustrates how it may function as an analytical tool.

The purpose of this paper is to explore how brand origin (BO) cues affect the consumer’s association of a new brand with BO learning and the subsequent effects on brand image (BO semiotics). An integrative theoretical framework is proposed that includes both processes.

The proposed model is based on analogical learning theory and triadic semiotic theory.

Two types of BO knowledge form BO meanings in consumer minds: country-related categories and exemplar brands, which have a classification and/or inferential role. The brand cues (indexes or icons) used by consumers to identify BO generate one or the other type of BO knowledge. Indexes trigger the classification function of country-related categories while icons trigger the inferential role of country-related categories and exemplar brands. BO knowledge informs the meaning transfer when consumers interpret the meaning of a new brand, leading to either a transfer of relations or a transfer of attributes to the new brand.

Marketers should monitor BO exemplar brands that consumers use as meaning sources and carefully select the signs used in their communications to evoke BO.

The proposed framework contrasts with dominant categorisation perspectives, re-establishing the dual role of categories and emphasising the relevance of brand cues in BO identification and BO exemplar brands in the BO meaning transfer process. A meaning-centred perspective is adopted to integrate BO identification and the related transfer mechanisms.

Drawing from the spillover effect literature, the purpose of this paper is to investigate the spillover effect in consumers’ web-mobile payment extension behavior. The authors figure out two categories of factors associated with the spillover effect: relevant schema and schematic fit. Cognitive trust and emotional trust in web payment are used to capture relevant schema, while perceived similarity and perceived business tie are proposed to denote schematic fit in the web-mobile payment extension context.

An online survey (n =552) was conducted to empirically test the model. The data were analyzed by structural equation modeling approach.

The results show that relevant schema and schematic fit factors positively influence perceived value of mobile payment (MP), which facilitates consumers’ behavioral intention of MP.

This study contributes to the extant literature by theoretically identifying the key factors of the spillover effect and empirically investigating its role during the web-mobile service extension process.

Puts forward a new method for decomposing relational schemas by using semi‐equivalence relations based on pansystems methodology. A necessary and sufficient condition is obtained for determining whether there exists a subschema logically available in a given relational schema decomposition.

The purpose of this paper is to present ontology alignment as a basis for mobile service integration and invocation.

This paper presents an automated schema‐based approach to align the ontologies from interacting devices as a basis for mobile service invocation. When the ontologies are ambiguous about the services provided, compatibility vectors are introduced as a means of maintaining ontology quality and deciding which service to choose to reduce the ambiguity.

Both precision and recall measurements are applied in the evaluation of the alignment approach, with promising results. In addition, for the compatibility vector system, it is not only proved theoretically that the approach is both precise and efficient, but it also shows promising results experimentally.

In cases where sufficient resources are not available and only a certain number of mobile devices can be chosen for interaction, this approach increases the efficiency by choosing suitable mobile device(s).

This current approach makes use of a center ontology, but introduces the problem of how to handle the vulnerability issue inherent in this centralized solution. To analyze and solve this problem is a potential research direction.

Mathematics can be a challenging content area for all students and especially for students with disabilities. Assistive technology can support the access, participation and achievement of students with disabilities in mathematics in general and in inclusive mathematics settings in particular. In this chapter, assistive technology to academic and functional mathematics will be discussed; particularly, manipulatives, calculators and other technology-mediated mathematics interventions (e.g., apps or computer programs) will be highlighted.

Most local governance assessment tools are entirely or partially based on stakeholders’ surveys, focus groups and benchmarks of different local governments in the world. These tools remain a subjective way of local governance evaluation. To measure the performance of local good-governance using an unbiased assessment technique, the authors have developed a framework to help automate the design process of a data warehouse (DW), which provides local and central decision-makers with factual, measurable and accurate local government data to help assess the performance of local government. The purpose of this paper is to propose the extraction of the DW schema based on a mixed approach that adopts both i* framework for requirements-based representation and domain ontologies for data source representation, to extract the multi-dimensional (MD) elements. The data was collected from various sources and information systems (ISs) deployed in different municipalities.

The authors present a framework for the design and implementation of a DW for local good-governance assessment. The extraction of facts and dimensions of the DW’s MD schema is done using a hybrid approach, where the extraction of requirement-based DW schema and source-based DW schema are done in parallel followed by the reconciliation of the obtained schemas to obtain the good-governance assessment DW final design.

The authors developed a novel framework to design and implement a DW for local good-governance assessment. The framework enables the extraction of the DW MD schema by using domain ontologies to help capture semantic artifacts and minimize misconceptions and misunderstandings between different stakeholders. The introduction and use of domain ontologies during the design process serves the generalization and automation purpose of the framework.

The presently conducted research faced two main limitations as follows: the first is the full automation of the design process of the DW and the second, and most important, is access to local government data as it remains limited because of the lack of digitally stored data in municipalities, especially in developing countries in addition to the difficulty of accessing the data because of regulatory aspects and bureaucracy.

The local government environment is among the public administrations most subject to change-adverse cultures and where the authors can face high levels of resistance and significant difficulties during the implementation of decision support systems, despite the commitment/engagement of decision-makers. Access to data sources stored by different ISs might be challenging. While approaching the municipalities for data access, it was done in the framework of a research project within one of the most notorious universities in the country, which gave more credibility and trust to the research team. There is also a need for further testing of the framework to reveal its scalability and performance characteristics.

Compared to other local government assessment ad hoc tools that are partially or entirely based on subjectively collected data, the framework provides a basis for automated design of a comprehensive local government DW using e-government domain ontologies for data source representation coupled with the goal, rationale and business process diagrams for user requirements representations, thus enabling the extraction of the final DW MD schema.