Representing the epistemic nature of teachers’ practical knowledge : The case of class teachers’ general pedagogy

The present study addressed the epistemology of teachers’ practical knowledge. Drawing from the literature, teachers’ practical knowledge is defined as all teachers’ cognitions (e.g., beliefs, values, motives, procedural knowing, and declarative knowledge) that guide their practice of teaching. The teachers’ reasoning that lies behind their practical knowledge is addressed to gain insight into its epistemic nature. I studied six class teachers’ practical knowledge; they teach in the metropolitan region of Helsinki. Relying on the assumptions of the phenomenographic inquiry, I collected and analyzed the data. I analyzed the data in two stages where the first stage involved an abductive procedure, and the second stage an inductive procedure for interpretation, and thus developed the system of categories. In the end, a quantitative analysis nested into the qualitative findings to study the patterns of the teachers’’ reasoning. The results indicated that teachers justified their practical knowledge based on morality and efficiency of action; efficiency of action was found to be presented in two different ways: authentic efficiency and naïve efficiency. The epistemic weight of morality was embedded in what I call “moral care”. The core intention of teachers in the moral care was the commitment that they felt about the “whole character” of students. From this perspective the “dignity” and the moral character of the students should not replaced for any other “instrumental price”. “Caring pedagogy” was the epistemic value of teachers’ reasoning in the authentic efficiency. The central idea in the caring pedagogy was teachers’ intentions to improve the “intellectual properties” of “all or most” of the students using “flexible” and “diverse” pedagogies. However, “regulating pedagogy” was the epistemic condition of practice in the cases corresponding to naïve efficiency. Teachers argued that an effective practical knowledge should regulate and manage the classroom activities, but the targets of the practical knowledge were mainly other “issues “or a certain percentage of the students. In these cases, the teachers’ arguments were mainly based on the notion of “what worked” regardless of reflecting on “what did not work”. Drawing from the theoretical background and the data, teachers’ practical knowledge calls for “praxial knowledge” when they used the epistemic conditions of “caring pedagogy” and “moral care”. It however calls for “practicable” epistemic status when teachers use the epistemic condition of regulating pedagogy. As such, praxial knowledge with the dimensions of caring pedagogy and moral care represents the “normative” perspective on teachers’ practical knowledge, and thus reflects a higher epistemic status in comparison to “practicable” knowledge, which represents a “descriptive” perception toward teachers’ practical knowledge and teaching.

Cervical headgear in Class II division 1 correction in children : Academic Dissertation

Class II division 1 malocclusion occurs in 3.5 to 13 percent of 7 12 year-old children. It is the most common reason for orthodontic treatment in Finland. Correction is most commonly performed using headgear treatment. The aim of this study was to investigate the effects of cervical headgear treatment on dentition, facial skeletal and soft tissue growth, and upper airway structure, in children. 65 schoolchildren, 36 boys and 29 girls were studied. At the onset of treatment a mean age was 9.3 (range 6.6 12.4) years. All the children were consequently referred to an orthodontist because of Class II division 1 malocclusion. The included children had protrusive maxilla and an overjet of more than 2mm (3 to 11 mm). The children were treated with a Kloehn-type cervical headgear as the only appliance until Class I first molar relationships were achieved. The essential features of the headgear were cervical strong pulling forces, a long upward bent outer bow, and an expanded inner bow. Dental casts and lateral and posteroanterior cephalograms were taken before and after the treatment. The results were compared to a historical, cross-sectional Finnish cohort or to historical, age- and sex-matched normal Class I controls. The Class I first molar relationships were achieved in all the treated children. The mean treatment time was 1.7 (range 0.3-3.1) years. Phase 2 treatments were needed in 52% of the children, most often because of excess overjet or overbite. The treatment decreased maxillary protrusion by inhibiting alveolar forward growth, while the rest of the maxilla and mandible followed normal growth. The palate rotated anteriorly downward. The expansion of the inner bow of the headgear induced widening of the maxilla, nasal cavity, and the upper and lower dental arches. Class II malocclusion was associated with narrower oro- and hypopharyngeal space than in the Class I normal controls. The treatment increased the retropalatal airway space, while the rest of the airway remained unaffected. The facial profile improved esthetically, while the facial convexity decreased. Facial soft tissues masked the facial skeletal convexity, and the soft tissue changes were smaller than skeletal changes. In conclusion, the headgear treatment with the expanded inner bow may be used as an easy and simple method for Class II correction in growing children.

Social-class inequalities in ill health - the contribution of physical workload

Tutkimuksen aiheita olivat yhteiskuntaluokkien väliset erot sairastavuudessa ja alentuneessa toimintakyvyssä, sekä fyysisen työkuormituksen ja joidenkin muiden työolojen vaikutus sairastavuuteen. Empiirisestä työstä on raportoitu myös neljässä kansainvälisissä tieteellisissä aikakauskirjoissa julkaistussa artikkelissa. Tässä julkaistu yhteenveto sisältää tulosten yhteenvedon lisäksi myös tutkimusta koskevien käsitteellisten ja teoreettisten kysymysten sekä tutkimustradition kriittisen katsauksen. Työn päätavoitteita olivat 1) tutkia fyysisesti kuormittavan työn, ja jossain määrin muiden työolojen osuutta yhteiskuntaluokkien välisiin eroihin sairaudessa ja toimintakyvyn alentuneisuudessa; 2) tutkia työn fyysisen kuormittavuuden, työhön liittyvien vaikutusmahdollisuuksien ja hallinnan (decision latitude), luokka-aseman, iän ja sukupuolen yhteisvaikutuksia heikentyneeseen terveydentilaan; sekä 3) tutkia missä määrin mekaanisten työaltisteiden ja tuki- ja liikuntaelinsairastavuuden välinen yhteys voi selittää yhteiskuntaluokkien välisiä eroja heikentyneessä yleisessä terveydentilassa. Tutkittavat olivat keski-ikäisiä Helsingin kaupungin työntekijöitä. Analyysit perustuivat poikittaisasetelmaan, ja käytetty aineisto oli Helsinki Health Studyn vuosien 2000 ja 2002 välillä kerättyä aineistoa. Analyyseihin käytetyssä aineistossa oli 3740:stä 8002:een tutkittavaa. Tulosten perusteella fyysisillä (sekä fysikaalisilla) työoloilla on merkittävä vaikutus yhteiskuntaluokkien välisiin eroihin yleisessä sairastavuudessa, toimintakyvyn heikentymisessä, tuki- ja liikuntaelinsairastavuudessa sekä itsearvioidussa terveydentilassa. Naisilla lähes puolet heikentyneen toimintakyvyn ja koetun terveydentilan luokkaeroista vaikutti olevan selitettävissä fyysisellä työkuormituksella. Hallintamahdollisuuksien ei havaittu merkittävästi muuttavan fyysisen kuormituksen vaikutusta toimintakykyyn. Fyysisen kuormittavuuden terveysvaikutus voimistui kasvavan iän mukaan enemmän naisilla kuin miehillä. Osa, mutta ei koko fyysisen kuormituksen vaikutus yhteiskuntaluokkien eroihin heikentyneessä terveydessä vaikutti välittyvän tuki- ja liikuntaelinsairastavuuden kautta. Terveys ja sairaus eivät ole yhtenäisiä tiloja, ja siksi monet eri sosiaalisesti ja rakenteellisesti määräytyvät olosuhteet todennäköisesti vaikuttavat yhteiskunnallisten terveyserojen syntymiseen. Fyysis-materiaalisten olojen vaikutusta terveyserojen syntyyn nyky-yhteiskunnassa on mahdollisesti aliarvioitu. Yhteiskuntaluokkien väliset erot fyysis-materiaalisissa olosuhteissa eivät ole kadonneet, ja nämä erot todennäköisesti vaikuttavat terveyserojen syntyyn.

Generalised regression estimation for domain class frequencies

This study examines the properties of Generalised Regression (GREG) estimators for domain class frequencies and proportions. The family of GREG estimators forms the class of design-based model-assisted estimators. All GREG estimators utilise auxiliary information via modelling. The classic GREG estimator with a linear fixed effects assisting model (GREG-lin) is one example. But when estimating class frequencies, the study variable is binary or polytomous. Therefore logistic-type assisting models (e.g. logistic or probit model) should be preferred over the linear one. However, other GREG estimators than GREG-lin are rarely used, and knowledge about their properties is limited. This study examines the properties of L-GREG estimators, which are GREG estimators with fixed-effects logistic-type models. Three research questions are addressed. First, I study whether and when L-GREG estimators are more accurate than GREG-lin. Theoretical results and Monte Carlo experiments which cover both equal and unequal probability sampling designs and a wide variety of model formulations show that in standard situations, the difference between L-GREG and GREG-lin is small. But in the case of a strong assisting model, two interesting situations arise: if the domain sample size is reasonably large, L-GREG is more accurate than GREG-lin, and if the domain sample size is very small, estimation of assisting model parameters may be inaccurate, resulting in bias for L-GREG. Second, I study variance estimation for the L-GREG estimators. The standard variance estimator (S) for all GREG estimators resembles the Sen-Yates-Grundy variance estimator, but it is a double sum of prediction errors, not of the observed values of the study variable. Monte Carlo experiments show that S underestimates the variance of L-GREG especially if the domain sample size is minor, or if the assisting model is strong. Third, since the standard variance estimator S often fails for the L-GREG estimators, I propose a new augmented variance estimator (A). The difference between S and the new estimator A is that the latter takes into account the difference between the sample fit model and the census fit model. In Monte Carlo experiments, the new estimator A outperformed the standard estimator S in terms of bias, root mean square error and coverage rate. Thus the new estimator provides a good alternative to the standard estimator.