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The aims of this collaborative research study between University of Cape Town and University of Sheffield study were to explore the contemporary play environments of children in order to identify the ways in which children’s play is shaped by technology, to examine the relationship between digital play, learning and creativity, and to explore the role of adults in mediating digital play. One of the five objectives was to understand the dynamics operating across the digital ecology of children’s play (in homes, communities and schools) in terms of synergies, dissonance and transfer, and to identify the implications for learning. The study adopted a mixed-methods approach. Parents of 3-11 year-olds were invited to complete a survey, and 30 parents then took part in telephone interviews in order to follow-up themes from the survey in greater detail. Case studies with families were undertaken. In the case studies, parents and children were interviewed and videoed. Parents also filmed their children using technologies, and they and their children were asked questions about the videos. Parents were invited to share images and videos with researchers using WhatsApp. In addition, children in the families were given diaries to record their use of social media and television, and used Go-Pro cameras to record their digital play. Further, children were invited to build a toy they would like to be invented using LEGO bricks. Children were invited to create concept maps on a number of questions relating to play, technology and learning. In addition, the children were observed in schools using technology, and were also observed in a regular after-school club or community venue they visited. In each case, the child’s class teacher and the community/ after school club leader were interviewed. Finally, children in schools took part in focus group interviews in which they were invited to create collages, complete concept maps and build a toy they would like to be invented using LEGO bricks. In this study, we started with 10 families (one family with twins) from 9 schools in the Cape Town area, that is, 11 case-study children (see Table 1), who were selected by the teachers and observed in school. After the school visits, one family (case-study child Fahiema) decided not to participate in the family visits part of the field work. The transcripts for each of the case-study children and the telephonic interviews of 30 parents on follow-up themes from the survey is shared. To protect identities of participants, pseudonyms are used. The following qualitative data is shared: interviews with their teachers; focus-group discussions; community visits; family visits and telephonic parent interviews. NOTE: The research instruments used in this study were adapted from Marsh, J. Stjerne Thomsen, B., Parry, B., Scott, F. Bishop, J.C., Bannister, C., Driscoll, A., Margary, T., Woodgate, A., (2019) Children, Technology and Play. UK Survey Questions. LEGO Foundation.
Data Types:
  • Dataset
Quantitative data for manuscript Higgins G, Peres J, Abdalrahman T, Zaman MH, Lang DM, Prince S, Franz T. Cytoskeletal tubulin competes with actin to increase deformability of metastatic melanoma cells. bioRxiv, 2020, 929919. One Excel file with four spread sheets:1) Cell shape data,2) Migration data, 3) Western blot data, and 4) Microrheology data.
Data Types:
  • Dataset
Julia Code to aid reproducibility for the paper: Malliavin-Mancino estimators implemented with the non-uniform fast Fourier transform. DOI for the Dataset: 10.25375/uct.11903442
Data Types:
  • Software/Code
R codes (not cleaned) for primary analyses for MSc project. Note supplemental and linked R codes and datasets can be requested. This code shows methodology running most analyses.
Data Types:
  • Dataset
The R code explores the calibration and simulation of the Farmer and Joshi (2002) agent-based model of financial markets using the method of moments along with a genetic algorithm and a Nelder-Mead with threshold accepting algorithm. The model is used for understanding daily trading decisions made from closing auction to closing auction in equity markets, as it attempts to model financial market behaviour without the inclusion of agent adaptation. However, our attempt at calibrating the model has limited success in replicating important stylized facts observed in financial markets, similar to what has been found in other calibration experiments of the model. This leads us to extend the Farmer-Joshi model to include agent adaptation using a Brock-Hommes (1998) approach to strategy fitness based on trading strategy profitability. The adaptive Farmer-Joshi model allows trading agents to switch between strategies, favouring strategies that have been more profitable over some period of time determined by a free-parameter determining the profit monitoring time-horizon.
Data Types:
  • Software/Code
The aims of this collaborative research study between University of Cape Town and University of Sheffield study were to explore the contemporary play environments of children in order to identify the ways in which children’s play is shaped by technology, to examine the relationship between digital play, learning and creativity, and to explore the role of adults in mediating digital play. One of the five objectives was to understand the dynamics operating across the digital ecology of children’s play (in homes, communities and schools) in terms of synergies, dissonance and transfer, and to identify the implications for learning. The study adopted a mixed-methods approach. Parents of 3-11 year-olds were invited to complete a survey, and 30 parents then took part in telephone interviews in order to follow-up themes from the survey in greater detail. Case studies with families were undertaken. In the case studies, parents and children were interviewed and videoed. Parents also filmed their children using technologies, and they and their children were asked questions about the videos. Parents were invited to share images and videos with researchers using WhatsApp. In addition, children in the families were given diaries to record their use of social media and television, and used Go-Pro cameras to record their digital play. Further, children were invited to build a toy they would like to be invented using LEGO bricks. Children were invited to create concept maps on a number of questions relating to play, technology and learning. In addition, the children were observed in schools using technology, and were also observed in a regular after-school club or community venue they visited. In each case, the child’s class teacher and the community/ after school club leader were interviewed. Finally, children in schools took part in focus group interviews in which they were invited to create collages, complete concept maps and build a toy they would like to be invented using LEGO bricks. In this study, we started with 10 families (one family with twins) from 9 schools in the Cape Town area, that is, 11 case-study children (see Table 1), who were selected by the teachers and observed in school. After the school visits, one family (case-study child Fahiema) decided not to participate in the family visits part of the field work. The transcripts for each of the case-study children and the telephonic interviews of 30 parents on follow-up themes from the survey is shared. To protect identities of participants, pseudonyms are used. The following qualitative data is shared: interviews with their teachers; focus-group discussions; community visits; family visits and telephonic parent interviews. NOTE: The research instruments used in this study were adapted from Marsh, J. Stjerne Thomsen, B., Parry, B., Scott, F. Bishop, J.C., Bannister, C., Driscoll, A., Margary, T., Woodgate, A., (2019) Children, Technology and Play. UK Survey Questions. LEGO Foundation.
Data Types:
  • Dataset
Quantitative data for manuscript Higgins G, Peres J, Abdalrahman T, Zaman MH, Lang DM, Prince S, Franz T. Cytoskeletal tubulin competes with actin to increase deformability of metastatic melanoma cells. bioRxiv, 2020, 929919. One Excel file with four spread sheets:1) Cell shape data,2) Migration data, 3) Western blot data, and 4) Microrheology data.
Data Types:
  • Dataset
Julia Code to aid reproducibility for the paper: Malliavin-Mancino estimators implemented with the non-uniform fast Fourier transform. DOI for the Dataset: 10.25375/uct.11903442
Data Types:
  • Software/Code
R codes (not cleaned) for primary analyses for MSc project. Note supplemental and linked R codes and datasets can be requested. This code shows methodology running most analyses.
Data Types:
  • Dataset
The R code explores the calibration and simulation of the Farmer and Joshi (2002) agent-based model of financial markets using the method of moments along with a genetic algorithm and a Nelder-Mead with threshold accepting algorithm. The model is used for understanding daily trading decisions made from closing auction to closing auction in equity markets, as it attempts to model financial market behaviour without the inclusion of agent adaptation. However, our attempt at calibrating the model has limited success in replicating important stylized facts observed in financial markets, similar to what has been found in other calibration experiments of the model. This leads us to extend the Farmer-Joshi model to include agent adaptation using a Brock-Hommes (1998) approach to strategy fitness based on trading strategy profitability. The adaptive Farmer-Joshi model allows trading agents to switch between strategies, favouring strategies that have been more profitable over some period of time determined by a free-parameter determining the profit monitoring time-horizon.
Data Types:
  • Software/Code