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The purpose of this study was to assess the Parents as Teachers program and its relationship to literacy and school readiness among kindergarten students enrolled in three elementary schools in southwestern New Mexico, using the Dynamic Indicators of Literacy Skills assessment system. Data were collected by trained teachers and parent volunteers and used by the Parents as Teachers program as part of their program evaluation. Analysis of these data showed that the PAT program is having positive results for participating students in this school district in comparison to non-PAT kindergartners. The overall results from this study support continuing implementation of the PAT program in this area because it appears that PAT children are entering school with sufficient literacy readiness skills based on the Fall 2005 and Spring 2006 outcome of the DIBELS assessment outcome.

Accountability for student learning outcomes is of importance to parents and school and district administrators, especially since the passage of The No Child Left Behind Act in 2001. The requirement for high-stakes testing to measure progress has fostered interest in ways to monitor student preparedness during the school year. This study used 2014 and 2015 test data from of 154 students from one elementary school to measure the correlation between individually administered Kaufman Test of Educational Achievement Brief Reading and DIBELS Next reading assessments and outcomes on the high-stakes Utah SAGE test. This correlational study used Pearson correlation coefficients to determine redundancy across the tests, and used multiple regression to assess how well scores on the KTEA and DIBELS Next tests predict students' subsequent scores on the SAGE test. Results indicate that DIBELS Next was a strong predictor of SAGE outcomes while KTEA Brief results were moderate predictors.

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xiii, 137 p. : ill. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / Research suggests that development of the alphabetic principle is a critical factor in learning to recognize words and becoming a successful reader. The alphabetic principle encompasses both the understanding that relationships exist between letters and sounds and the application of these relationships to reading words. This study investigated the degree to which different measures of the alphabetic principle were predictive of later reading development. These measures were examined in the context of Ehri's phase theory of sight word development to investigate how different behaviors associated with the alphabetic principle fit within a developmental framework. Two cohorts of students (109 kindergarteners, 212 first graders) participated in this study from spring of 2007 until late fall of 2008 (58 second graders, 121 third graders). The predictive powers of single and combined measures of the alphabetic principle were analyzed using sequential regression. Results indicated that each measure explained significant between-student variation in performance on measures of word reading fluency, oral reading fluency (ORF), vocabulary, and reading comprehension. A measure of letter-sounds embedded in nonsense words appeared to have more utility for the prediction of reading outcomes than a measure of letter-sounds presented in isolation. Additionally, including a measure of nonsense words with a measure of letter-sounds embedded in nonsense words increased the predictive power of the model over and above the predictive power of letter sounds alone. Growth on ORF served as an additional criterion for the purpose of investigating the methodology of measuring growth. Two conceptualizations of growth were explored: raw score change over time and individual rates of growth over time (slope). Correlations and sequential regression were used to evaluate the relationship between raw score change and measures of the alphabetic principle. Hierarchical Linear Modeling (HLM) was used to model individual slopes on Lexile measures of ORF (LORF). In general, raw score change appeared largely unrelated to measures of the alphabetic principle. HLM analyses revealed that individual differences in slope on LORF were minimal and not very reliable, making the prediction of these differences difficult. Recommendations for future research and implications for practice are discussed. / Committee in charge: Roland Good, Chairperson, Special Education and Clinical Sciences; Kenneth Merrell, Member, Special Education and Clinical Sciences; Leanne Ketterlin Geller, Member, Educational Methodology, Policy, and Leadership; Jean Stockard, Outside Member, Planning Public Policy and Management

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Abstract Achieving the objective of a decarbonised economy by 2050 will require massive efforts in the energy sector. Emissions from residential houses will have to be almost completely cut, by around 90% by 2050. Home automation is a potential tool for achieving this goal. However, the environmental and economic benefits of automation technologies first need to be assessed. This thesis evaluates the impact of home automation for electricity management in the residential sector using environmental and economic indicators. To this end, a life cycle assessment was performed to evaluate the impacts of the manufacturing, use and disposal phases. The influences of end-user behaviour, household size and multiple levels of technological deployment were also investigated. A Markov chain simulation tool, built on the MatLab platform, was developed to assess all possible combinations of impacting factors. Dynamic environmental indicators were developed based on the ReCiPe method for aggregating the impacts of processes. All these indicators were then combined to form a single index based on multi-criteria acceptability analysis. The results suggest that home automation can decrease peak load, but that overall electricity consumption may increase due to electricity use by the actual automation system. The effect of home automation was more noticeable in larger households than in one-person households. In addition, use of dynamic environmental indicators proved more relevant than fixed indicators to represent the environmental impact of home automation. Within the life cycle of automation technology, the manufacturing phase had the highest impact, but most of the CO2 emissions originated from the use phase. In conclusion, the most important environmental benefit of home automation is reducing CO2 emissions during peak time by load shifting. / Tiivistelmä Vähähiilisen talouden saavuttaminen vuoteen 2050 mennessä edellyttää valtavia ponnisteluja energia-alalla. Rakennuksista aiheutuvia päästöjä on vähennettävä radikaalisti, jopa 90 % vuoteen 2050 mennessä. Rakennusten energiatehokkuutta edistävä automaatiotekniikka on yksi keino tämän päämäärän saavuttamiseen. Kotiautomaation kautta voidaan sekä vähentää energian kokonaiskulutusta että tasoittaa energiankäyttöprofiilia. On kuitenkin tutkittava myös, mitkä ovat automaatiotekniikan ympäristö- ja taloudelliset vaikutukset. Tässä työssä käsitellään kotiautomaation vaikutusta sähkön kulutuksen hallintaan asuinrakennuksissa käyttämällä ympäristö- ja talousindikaattoreita. Tätä varten suoritettiin kotiautomaation elinkaariarviointi selvittämällä laitteiden valmistus-, käyttö- ja hävittämisvaiheiden ympäristövaikutukset. Työssä tarkasteltiin myös asukkaiden käyttäytymisen, kotitalouden koon ja eri teknologiavaihtoehtojen vaikutuksia ympäristö- ja talousvaikutuksiin. Arviointi suoritettiin Markovin ketjun simulointityökalulla, joka rakennettiin Matlab-alustalle. Dynaamisia ympäristömittareita kehitettiin ReCiPe-menetelmää käyttäen. Indikaattorit on edelleen yhdistetty yhdeksi indeksiksi käyttäen monikriteeriarviointia. Tulokset viittaavat siihen, että huippukuormitusta voidaan vähentää käyttämällä kotiautomaatiota, mutta sähkön kokonaiskulutus voi kasvaa automaatiojärjestelmän sähkönkulutuksen takia. Kotiautomaation vaikutukset ovat eniten havaittavissa suurissa kotitalouksissa. Lisäksi, dynaamiset indikaattorit edustavat paremmin kotiautomaation vaikutusta ympäristöön kuin staattiset indikaattorit. Automaatioteknologian elinkaaressa suurimmat ympäristövaikutukset ovat valmistusvaiheessa, mutta CO2-päästöjä syntyy eniten käyttövaiheessa. Lopuksi voidaan todeta, että kotiautomaation merkittävin ympäristöhyöty on CO2-päästöjen vähentäminen huippukulutuksen aikana siirtämällä kuormitusta toiseen ajankohtaan.