XXI. Internationale Erziehungskonferenz,UNESCO/BIE, (Methoden internationaler pädagogischer Zusammenarbeit) Genf,Juli 1958

Ohne Zusammenfassung     

SOCIAL DETERMINANTS AND POTENTIALS OF EDUCATION IN LATER LIFE: THE CASE OF AUSTRIA

Various theoretical concepts such as plasticity, competence, and potential have recently been applied to underline the possibility of later‐life development and change. Value and limitations of these concepts are discussed in view of learning in later life. A review of the special case of Austria and the educational attainments of its elderly indicates that social reality is slow in its transformation and that the disadvantageous educational achievements credited to today's older people hardly encourage them in pursuing later‐life studies. The paper reports results obtained by means of two questionnaires filled out by older students and teachers. This empirical investigation examines the influence of societal norms, social setting in institution‐related learning situations (age‐homogeneity vs. age‐heterogeneity), and instructors’ attitudes toward older students. The results demonstrate that permanent education and proper stimulation of the learning processes depend on a complex relationship between (competent) individuals, their social surroundings, and learning conditions that often prove unfavorable.     

An analysis of the needs for nonacademic staff and operating funds in a university

Regressions can be used to analyze the relationship between departmental activities and the need for nonacademic staff and operating funds. Support costs are broken into task categories and related to certain basic variables describing the composition and activity of the unit (e.g., FTE academic staff, teaching load). The results are then linked in a total model which predicts the cost for departmental support based on institutional activity variables. Beside the number of students, there are other variables such as the number of fields of study, number of teaching and research staff, and the laboratory equipment. The model is generalizable to many national settings.Presented at the Twentieth Annual Forum of the Institution for Institutional Research, April 1980.     

Travelling the Unpaved Road to Democracy from Communism: A Cross‐Cultural Perspective on Change

The basic subject of this article is change, how one copes with it, how it can or cannot be guided. More specifically, the author, a Czech‐American scholar, examines the processes and the trauma of the post‐1989 transition in his country of birth with an eye to how education, particularly higher education, can contribute to a successful outcome to transition affecting all of society while undergoing transition itself. Crucial to the presentation and arguments of the author is his conviction that the period of communist rule in Czechoslovakia, as in the other central and eastern European countries, was intellectually and morally damaging. For the citizens of the Czech Republic as well as for those of the other central and eastern European countries who also experienced communism and who are now trying to recover from it, it is necessary that they develop a clear understanding of what communism really represented and what it did to them. For them to gain this understanding, the catharsis that goes with it, and the possibility of developing successful reforms that will move their countries forward in a constructive way, they must develop a number of cross‐cultural skills through familiarity with a number of social science and educational disciplines that were more‐or‐less closed to them. The author proposes ways in which these skills can be learned and education at all levels profoundly reformed.     

E-learning with multiple-try-feedback: Can hints foster students’ achievement during the semester?

Educational technology research and development - E-learning opportunities have become an increasingly important component of university education. Various laboratory studies have shown that...     

Erscheinungsbasierte statistische Objekterkennung

Zusammenfassung.   Die automatische Erkennung und Lokalisation von Objekten in digitalen Bildern ist ein wesentlicher Bestandteil vieler praktisch relevanter Anwendungen. In diesem Artikel wird ein erscheinungsbasiertes Verfahren zur Erkennung starrer zwei- oder dreidimensionaler Objekte vorgestellt, dem eine statistische Modellierung zugrundeliegt. Im Gegensatz zu segmentierungsbasierten Verfahren, wie sie vor allem im Bereich der 3D-Objekterkennung eingesetzt werden, erm?glicht der erscheinungsbasierte Ansatz aufgrund der Modellierung der Intensit?tswerte oder davon abgeleiteter lokaler Merkmale eines Bildes die Erkennung komplexer Objekte. Die statistische Formulierung der Problemstellung bildet den mathematischen Kontext zur Bestimmung optimaler L?sungen. Die Form der Modellierung erlaubt neben der Einzelobjekterkennung auch die Berücksichtigung von heterogenem Bildhintergrund und Mehrobjektszenen. Die dazu ben?tigten lokalen Merkmale entstehen durch r?umlich begrenzte Transformationen des Bildes, wie beispielsweise Gabor- oder Wavelet-Transformationen. Die statistische Modellierung beschreibt die Verteilung dieser lokalen Merkmale anhand einer Dichtefunktion, die sich bei der Hintergrund- und Mehrobjektmodellierung als Mischungsverteilung der Einzelobjektverteilungen ergibt. Die Aufgabenstellungen des Erlernens und Erkennens von Objekten sind damit als Parametersch?tzprobleme formal darstellbar. Dabei werden im einen Fall die Modellparameter und im anderen Fall die Lageparameter beziehungsweise die Klassen von Objekten gesch?tzt. Die experimentelle überprüfung des Ansatzes anhand realer Objektaufnahmen durch CCD-Kameras zeigt seine Brauchbarkeit zur Erkennung von 2D- und 3D-Objekten bei homogenem und heterogenem Hintergrund. Eingegangen am 5. April 2000 / Angenommen am 20. Juli 2001     

One size fits all?: Towards a differentiated regional innovation policy approach

Innovation has moved to the foreground in regional policy in the last decade. Concrete policies were shaped by “best practice models” derived from high-tech areas and well performing regions. These are often applied in a similar way across many types of regions. Here an attempt is made to show that there is no “ideal model” for innovation policy as innovation activities differ strongly between central, peripheral and old industrial areas. In this paper we analyse different types of regions with respect to their preconditions for innovation, networking and innovation barriers. Based on this classification different policy options and strategies are developed.