title: Data transformation: a semantically-based approach to function discovery

authors: Phan, Thong H.

subjects: Function discovery

abstract: This paper presents the method of data transformation for discovering numeric functions from their examples. Based on the idea of transformations between functions, this method can be viewed as a semantic counterpart to the more common approach of formula construction used in most previous discovery systems. Advantages of the new method include a flexible implementation through the design of transformation rules, and a sound basis for rigorous mathematical analysis to characterize what can be discovered. The method has been implemented in a discovery system called "LINUS," which can identify a wide range of functions: rational functions, quadratic relations, and many transcendental functions, as well as those that can be transformed to rational functions by combinations of differentiation, logarithm and function inverse operations.

text: Data transformation: a semantically-based approach to function discovery This paper presents the method of data transformation for discovering numeric functions from their examples. Based on the idea of transformations between functions, this method can be viewed as a semantic counterpart to the more common approach of formula construction used in most previous discovery systems. Advantages of the new method include a flexible implementation through the design of transformation rules, and a sound basis for rigorous mathematical analysis to characterize what can be discovered. The method has been implemented in a discovery system called "LINUS," which can identify a wide range of functions: rational functions, quadratic relations, and many transcendental functions, as well as those that can be transformed to rational functions by combinations of differentiation, logarithm and function inverse operations.

year: 1994-08

title: A Meta-Analysis of interventions to reduce disruptive behaviour in classroom settings

authors: Frame, Belinda

subjects: classroom management

abstract: I conducted a meta-analysis of 48 single-case and small-group experimental design studies from 1997 to 2024 that investigated interventions to reduce disruptive behaviour in classroom settings. I extracted data from graphs displaying behavioural data resulting from interventions to reduce disruptive behaviour and then I calculated Tau-U effect sizes. A total of 180 effect sizes from the 48 studies produced a total mean effect size of -0.82 indicating that 82% of students experienced a reduction in their disruptive behaviour. Interventions designed for individual students produced a very large mean effect size (ES = -0.85, SD = 0.31) compared to class-wide strategies (ES = -0.76, SD = 0.30). The most prevalent intervention was group contingencies included in 13 studies. The most utilised intervention within this group was the Good Behaviour Game. All interventions provided in the studies included in this meta-analysis resulted in a reduction in disruptive behaviour, however not all interventions had a strong representation across the studies and therefore have limitations. A small number of experiments trialling an intervention may produce a large effect size, however, due to the need for replication to evoke confidence in the efficacy of an intervention, these results are tentative at best. There is also a strong theme for more training for teachers in classroom management skills as many teachers are reporting that they are not equipped for managing disruptive behaviour in the classroom.

text: A Meta-Analysis of interventions to reduce disruptive behaviour in classroom settings I conducted a meta-analysis of 48 single-case and small-group experimental design studies from 1997 to 2024 that investigated interventions to reduce disruptive behaviour in classroom settings. I extracted data from graphs displaying behavioural data resulting from interventions to reduce disruptive behaviour and then I calculated Tau-U effect sizes. A total of 180 effect sizes from the 48 studies produced a total mean effect size of -0.82 indicating that 82% of students experienced a reduction in their disruptive behaviour. Interventions designed for individual students produced a very large mean effect size (ES = -0.85, SD = 0.31) compared to class-wide strategies (ES = -0.76, SD = 0.30). The most prevalent intervention was group contingencies included in 13 studies. The most utilised intervention within this group was the Good Behaviour Game. All interventions provided in the studies included in this meta-analysis resulted in a reduction in disruptive behaviour, however not all interventions had a strong representation across the studies and therefore have limitations. A small number of experiments trialling an intervention may produce a large effect size, however, due to the need for replication to evoke confidence in the efficacy of an intervention, these results are tentative at best. There is also a strong theme for more training for teachers in classroom management skills as many teachers are reporting that they are not equipped for managing disruptive behaviour in the classroom.

year: 2025

title: "He Matapihi ki te Mana Raraunga” - Conceptualising Big Data through a Māori lens

authors: Hudson, Maui

abstract: Advances in computer technology and analytical processes create an environment where data becomes the raw material mined to create valuable information and insights. The idea of Big Data emerges from the collation of increasing vast amounts of data enabled by the shift towards an increasingly open data environment. How this changing context alters the relationship between Iwi/Māori collectives and their mātauranga, cultural information and data has yet to be fully explored. However, the concept of Māori Data Sovereignty, which anticipates Māori governance over Māori data, has a natural appeal. This chapter outlines some of the Māori concepts and presents a framework which may be used to inform how data and data use may be conceptualised through a Māori cultural lens.

text: "He Matapihi ki te Mana Raraunga” - Conceptualising Big Data through a Māori lens Advances in computer technology and analytical processes create an environment where data becomes the raw material mined to create valuable information and insights. The idea of Big Data emerges from the collation of increasing vast amounts of data enabled by the shift towards an increasingly open data environment. How this changing context alters the relationship between Iwi/Māori collectives and their mātauranga, cultural information and data has yet to be fully explored. However, the concept of Māori Data Sovereignty, which anticipates Māori governance over Māori data, has a natural appeal. This chapter outlines some of the Māori concepts and presents a framework which may be used to inform how data and data use may be conceptualised through a Māori cultural lens.

year: 2017