Anesa Hosein
I am currently at the University of Surrey as a Lecturer in Higher Education where I'm teaching on the Graduate Certificate in Learning and Teaching. I am also helping to put together a MA in Higher Education which should run in 2014/15. I work with various persons in different faculties to help improve their teaching and learning.
I am still continuing my research in mathematics education and research methods pedagogy. I'm currently working on a project at investigating why students choose to do a STEM subject at the university level with Alice Sullivan from the IOE. This project is funded by a British Academy Skills Acquisition Grant. I am also working with Namrata Rao on developing research methods OERs which is funded by the HEA CLL funding strand.
I was previously at Liverpool Hope Faculty taught mathematics and education courses. I was also a Research Assistant on the Net Generation project sponsored by the ESRC at the Open University (Team Leader: Chris Jones). We looked at the way HE students from the Net Generation and non-Net Generation use technological tools for learning and leisure.
I am interested in understanding how students learn mathematics when using software. My main interests lie in understanding students' learning through cognitive psychology and investigating how attitudes may influence learning. In particular, I've used theories related to self-explanation, deep/surface learning and self-confidence.
Otherwise than my interest in mathematics, I have conducted a number of internet-oriented research such as online surveys. The most noteworthy purely internet data collection is the audio/video recording of students' interaction with software through a method/protocol I tested and called web-conferencing remote observation. This requires using webcams, microphones and application sharing software.
Supervisors: Doug Clow, James Aczel, and John Richardson
I am still continuing my research in mathematics education and research methods pedagogy. I'm currently working on a project at investigating why students choose to do a STEM subject at the university level with Alice Sullivan from the IOE. This project is funded by a British Academy Skills Acquisition Grant. I am also working with Namrata Rao on developing research methods OERs which is funded by the HEA CLL funding strand.
I was previously at Liverpool Hope Faculty taught mathematics and education courses. I was also a Research Assistant on the Net Generation project sponsored by the ESRC at the Open University (Team Leader: Chris Jones). We looked at the way HE students from the Net Generation and non-Net Generation use technological tools for learning and leisure.
I am interested in understanding how students learn mathematics when using software. My main interests lie in understanding students' learning through cognitive psychology and investigating how attitudes may influence learning. In particular, I've used theories related to self-explanation, deep/surface learning and self-confidence.
Otherwise than my interest in mathematics, I have conducted a number of internet-oriented research such as online surveys. The most noteworthy purely internet data collection is the audio/video recording of students' interaction with software through a method/protocol I tested and called web-conferencing remote observation. This requires using webcams, microphones and application sharing software.
Supervisors: Doug Clow, James Aczel, and John Richardson
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Books by Anesa Hosein
Three approaches that students may undertake when solving the tasks were investigated: students' processing levels, their software exploration and their self-explanations. The effect of mathematics confidence on students' approaches and performance was also considered.
Thirty-eight students were randomly assigned to one of the software boxes in an experimental design where all audio and video data were collected via a web-conference remote observation method. The students were asked to think-aloud whilst they solved three task types. The three task types were classified based on the level of conceptual and procedural knowledge needed for solving: mechanical tasks required procedural knowledge, interpretive tasks required conceptual knowledge; and constructive tasks used both conceptual and procedural knowledge.
The results indicated that the relationship between students' approaches and performance varied with the software box. Students using the black-box software explored more for the constructive tasks than the students in the glass-box and open-box software. These black-box software students also performed better on the constructive tasks, particularly those with higher mathematics confidence. The open-box software appeared to encourage more mathematical explanations whilst the glass-box software encouraged more real-life explanations.
Mathematically confident students were best able to appropriate the black-box software for their conceptual understanding. The glass-box software or open-box software appeared to be useful for helping students with procedural understanding and familiarity with mathematical terms.
Papers by Anesa Hosein
Three approaches that students may undertake when solving the tasks were investigated: students' processing levels, their software exploration and their self-explanations. The effect of mathematics confidence on students' approaches and performance was also considered.
Thirty-eight students were randomly assigned to one of the software boxes in an experimental design where all audio and video data were collected via a web-conference remote observation method. The students were asked to think-aloud whilst they solved three task types. The three task types were classified based on the level of conceptual and procedural knowledge needed for solving: mechanical tasks required procedural knowledge, interpretive tasks required conceptual knowledge; and constructive tasks used both conceptual and procedural knowledge.
The results indicated that the relationship between students' approaches and performance varied with the software box. Students using the black-box software explored more for the constructive tasks than the students in the glass-box and open-box software. These black-box software students also performed better on the constructive tasks, particularly those with higher mathematics confidence. The open-box software appeared to encourage more mathematical explanations whilst the glass-box software encouraged more real-life explanations.
Mathematically confident students were best able to appropriate the black-box software for their conceptual understanding. The glass-box software or open-box software appeared to be useful for helping students with procedural understanding and familiarity with mathematical terms.