This dissertation develops a word bank based on a series of well defined filters. The basis of this system is grapheme-phoneme relative frequency control. The word bank is designed to be used in developing reading materials at varied degrees of difficulty. Four short stories were edited as to their grapheme-phoneme relationships. Reading speed and reading comprehension were measured for each student on these stories. All students read a story in the original form and a story in the filtered version. No difference in reading comprehension were found, but reading speed was significantly higher on three of four stories.

Two hardware factors contributing to the overall image quality of digital CR Ts are display resolution and addressability. The relationship between these two factors and human performance was modeled by a metric of display quality, the Resolution Addressability Ratio (RAR), and investigated within the contexts of Word-Processing (WP) and Computer-Aided-Drafting (CAD) tasks. The findings indicate a perceptual limit to MTF bandwidth improvements, and significant differences iii display quality requirements between the two applications. The regression of image quality as a function of RAR metric values resulted in an r2 = 0.94 for the WP task and an r2 = 0.79 for the CAD task. These findings are discussed in terms of engineering guidelines for the design of CRT and flat-panel displays for applications which vary by the amount of the density of information in their typical displays.

Research shows that pupils experience difficulties with the word problems in their mathematical textbooks. The forms of representations are made visible through the word problems and are vital elements considering the pupils’ understanding of the basic idea of important concepts. The purpose of this study is to provide knowledge about how word problems in mathematical textbooks and their forms of representations can be used by pupils’ as a linguistic tool. Moreover, this research has used a quantitative content analysis where two different textbooks, their word problems and the forms of representations have been analyzed and quantified. The result shows that almost every word problem uses the representation of symbols. Furthermore, the majority of the word problems use the representation of real situations while the representation of picture is less evident. The result also shows that mathematical textbooks can be seen as a linguistic tool for the pupils since mathematical concepts often are expressed through different forms of representation. As a suggestion, teachers’ can complement their mathematical textbooks with external assignments based on the representations of picture situations to develop the pupils’ understanding. / Forskning visar på att elever har svårigheter med läroböckers textbaserade uppgifter. I textbaserade uppgifter synliggörs representationsformer som kan koppla samman med elevers förståelse för matematiska begrepp. Arbetet syftar till att bidra med kunskap kring hur tryckta läroböckers textbaserade uppgifter och deras representationsformer kan ses som ett språkligt stöd i elevernas lärande. Genom en kvantitativ innehållsanalys har två tryckta läroböckers textbaserade uppgifter och deras representationsformer analyserats och kvantifierats.Resultatet visar att nästintill alla de textbaserade uppgifterna använder sig av representationsformen symbol. Majoriteten av de textbaserade uppgifterna använder verkliga situationer. Medan färre textbaserade uppgifter använder sig av den bildliga representationsfomen. Läroböckerna kan ses som ett språkligt stöd för eleven där matematiska begrepp ofta uttrycks genom olika representationsformer. Förslagsvis kan lärare komplettera läroböckerna med egna bildliga representationsformer för att öka elevernas förståelse.

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When people predict recognition performance, they wrongly predict that high frequency words will produce better recognition than low frequency words. To examine whether familiarity was the heuristic behind these inaccurate predictions, participants saw some words prior to study to increase their familiarity. We found that familiarity influences predictions, but word frequency has the greater influence. Research has shown that these inaccurate predictions can be corrected with test experience. Subsequent predictions are more accurate, but it is unclear whether participants learn that low frequency words are always better for memory or that participants had learned that low frequency words are only better for recognition and high frequency words are better for recall. We resolved this issue by giving a forced-choice recognition test after the single-item recognition test to determine what participants learned after the first test, and we found that participants learned that low frequency words facilitate recognition but not recall.

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This dissertation explores an unintended consequence of using personalized recommendations, that is, recommendations that are targeted to an individual consumer (e.g., personalized music playlists). I conceptualize that using personalized recommender systems can impede consumers’ learning of their own preferences and tastes from product experiences. Therefore, using these systems can decrease preference clarity, which is defined as certainty about individuals’ own preferences. For example, people may feel less certain about their own music preferences after listening to auto-generated personalized playlists. This reduced preference clarity, in turn, reduces consumer willingness to generate word-of-mouth (WOM) about their consumption experiences, such as their intent to talk about music they listened to with others, or to post social media content on their favorite musicians. Eight studies, using correlational and experimental designs and conducted with consumers who actively use personalization services (in the fashion and music domains), support this theorization. I end with a discussion of the potential theoretical extensions of this novel finding, as well as its practical implications.

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