Curriculum guide for teaching sex education to 11 to 12 year old hearing impaired adolescents

This paper reviews a curriculum for sex education that is geared towards hearing impaired adolescents.

An educational curriculum outline for teaching sound and hearing in elementary schools

This paper provides curriculum on noise, ears, hearing and deafness for elementary school children.

Primary level curriculum units based on the Simple Sentence TAGS

This paper presents four teaching curriculum units for primary level students based on Simple and Complex TAGS (Teacher Assessment of Grammatical Structures), teaching vocabulary and language structure.

Icing on the Cake: Idiom curriculum for deaf and hard of hearing students

A look at the prevalence of idiom usage in the mainstream classroom, and the students' who are deaf/hard of hearing acquisition of idiom comprehension and usage. A complete teacher’s guide, including lesson plans and materials, and a list of idiom teaching resources for teachers of the deaf and mainstream teachers.

A theme-based creative movement curriculum for deaf and hard of hearing students: Focus on speech, language and audition skills

The purpose of this study was to develop a theme based creative movement curriculum that would help hearing-impaired students develop language, speech and audition skills.

A preschool hearing-impaired math curriculum

This paper presents a basic math curriculum for preschool hearing impaired children, including lesson plans and activities.

Semantic-level Visual Content Descriptor combining visual and textual cues as collaterals

In this paper, we introduce a novel high-level visual content descriptor which is devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt to bridge the so called “semantic gap”. The proposed image feature vector model is fundamentally underpinned by the image labelling framework, called Collaterally Confirmed Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts of the images with the state-of-the-art low-level image processing and visual feature extraction techniques for automatically assigning linguistic keywords to image regions. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicates that our proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models.