title: Automating vocabulary tests and enriching online courses for language learners

authors: König, Jemma Lynette

subjects: Computer science

abstract: The past decade has seen a massive growth in online academic courses, most of which are offered in the English language. However, although more people speak English as their second language than as their first, online course providers do not offer language assistance. Providing online learners with language resources would allow them to both learn about a subject through a foreign language and learn the foreign language through the subject. This is referred to as “content-based language learning”. 

Supporting content-based language learning using online courses raises several challenges, three of which are addressed in this thesis. First, courses teach subjects in particular domains, but supporting domain-specific language requires knowledge of specialised vocabulary. This thesis develops an automated approach to generating domain-specific corpora and wordlists, extracting domain-specific vocabulary in a way that can be applied to any online course. 

Second, acquiring and measuring language come hand-in-hand. Tools that help learners acquire new language should also include methods for testing. This thesis takes an existing vocabulary test and automates it. This has two main advantages: it requires no assumed knowledge of the language, allowing automatic generation of vocabulary tests; and the tests reflect the wordlists used to create them, allowing them to be targeted toward a particular domain.

Finally, for content-based language learning to be used successfully, the language components must be smoothly integrated into courses without disturbing the original content. Furthermore, vocabulary support should include multi-word lexical items as well as single words. The thesis describes a tool that enhances online course content, via a browser extension. It is completely automated, though would also lend itself to selective teacher intervention. It is illustrated here with reference to courses offered by the FutureLearn MOOC consortium.

text: Automating vocabulary tests and enriching online courses for language learners The past decade has seen a massive growth in online academic courses, most of which are offered in the English language. However, although more people speak English as their second language than as their first, online course providers do not offer language assistance. Providing online learners with language resources would allow them to both learn about a subject through a foreign language and learn the foreign language through the subject. This is referred to as “content-based language learning”. 

Supporting content-based language learning using online courses raises several challenges, three of which are addressed in this thesis. First, courses teach subjects in particular domains, but supporting domain-specific language requires knowledge of specialised vocabulary. This thesis develops an automated approach to generating domain-specific corpora and wordlists, extracting domain-specific vocabulary in a way that can be applied to any online course. 

Second, acquiring and measuring language come hand-in-hand. Tools that help learners acquire new language should also include methods for testing. This thesis takes an existing vocabulary test and automates it. This has two main advantages: it requires no assumed knowledge of the language, allowing automatic generation of vocabulary tests; and the tests reflect the wordlists used to create them, allowing them to be targeted toward a particular domain.

Finally, for content-based language learning to be used successfully, the language components must be smoothly integrated into courses without disturbing the original content. Furthermore, vocabulary support should include multi-word lexical items as well as single words. The thesis describes a tool that enhances online course content, via a browser extension. It is completely automated, though would also lend itself to selective teacher intervention. It is illustrated here with reference to courses offered by the FutureLearn MOOC consortium.

year: 2019

title: Testing a biologically-based system for extracting depth from brief monocular 2-D video sequences

authors: Perrone, John A.

subjects: Cameras

abstract: Knowledge of the 3-D layout in front of a moving robot or vehicle is essential for obstacle avoidance and navigation. Currently the most common methods for acquiring that information rely on ‘active’ technologies which project light into the world (e.g., LIDAR). Some passive (non-emitting) systems use stereo cameras but only a relatively small number of techniques attempt to solve the 3-D layout problem using the information from a single video camera. A single camera offers many advantages such as lighter weight and fewer video streams to process. The visual motion occurring in brief monocular video sequences contains information regarding the movement of the camera and the structure of the scene. Extracting that information is difficult however because it relies on accurate estimates of the image motion velocities (optical flow) and knowledge of the camera motion, especially the heading direction. We have solved these two problems and can now obtain image flow and heading direction using mechanisms based on the properties of motion sensitive neurones in the brain. This allows us to recover depth information from monocular video sequences and here we report on a series of tests that assess the accuracy of this novel approach to 3-D depth recovery.

text: Testing a biologically-based system for extracting depth from brief monocular 2-D video sequences Knowledge of the 3-D layout in front of a moving robot or vehicle is essential for obstacle avoidance and navigation. Currently the most common methods for acquiring that information rely on ‘active’ technologies which project light into the world (e.g., LIDAR). Some passive (non-emitting) systems use stereo cameras but only a relatively small number of techniques attempt to solve the 3-D layout problem using the information from a single video camera. A single camera offers many advantages such as lighter weight and fewer video streams to process. The visual motion occurring in brief monocular video sequences contains information regarding the movement of the camera and the structure of the scene. Extracting that information is difficult however because it relies on accurate estimates of the image motion velocities (optical flow) and knowledge of the camera motion, especially the heading direction. We have solved these two problems and can now obtain image flow and heading direction using mechanisms based on the properties of motion sensitive neurones in the brain. This allows us to recover depth information from monocular video sequences and here we report on a series of tests that assess the accuracy of this novel approach to 3-D depth recovery.

year: 2018

title: Hangarau me te Māori: Māori and technology

authors: Keegan, Te Taka Adrian Gregory

subjects: Māori

abstract: A sign of a vibrant, healthy developing nation is the adaptation and uptake of new technologies. Māori have a long, but mostly unrecognised, history of ingenious innovation and adaption of new technologies. This chapter will reveal Māori ingenuity through discussion of historic examples and modern media usages by Māori, and the future implications these have for Māori.
Technology can be defined as tools, devices and machines that have been developed by the application of scientific knowledge. Māori technology, then, is Māori tools, devices and machines that have been developed by the application of Māori scientific knowledge. This chapter discusses some examples of innovative Māori technology and their adoption in both historic and modern times. It includes sections on historic Māori technology, Māori media innovation and Māori adoption of Internet technology. Two sections are further expanded on: Māori in social networking sites and te reo Māori in technology. The chapter concludes with the authors' thoughts on how the adoption of new technologies will shape tikanga Māori and te reo Māori into the future.

text: Hangarau me te Māori: Māori and technology A sign of a vibrant, healthy developing nation is the adaptation and uptake of new technologies. Māori have a long, but mostly unrecognised, history of ingenious innovation and adaption of new technologies. This chapter will reveal Māori ingenuity through discussion of historic examples and modern media usages by Māori, and the future implications these have for Māori.
Technology can be defined as tools, devices and machines that have been developed by the application of scientific knowledge. Māori technology, then, is Māori tools, devices and machines that have been developed by the application of Māori scientific knowledge. This chapter discusses some examples of innovative Māori technology and their adoption in both historic and modern times. It includes sections on historic Māori technology, Māori media innovation and Māori adoption of Internet technology. Two sections are further expanded on: Māori in social networking sites and te reo Māori in technology. The chapter concludes with the authors' thoughts on how the adoption of new technologies will shape tikanga Māori and te reo Māori into the future.

year: 2018