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How to support primary teachers' implementation of inquiry: Teachers' reflections on teaching cooperative inquiry-based science

Science teachers

Gillies RM, Nichols K.
GSID: S9yvLqsUklMJ
RM Gillies, K Nichols - Research in Science Education, 2015 - Springer

Many primary teachers face challenges in teaching inquiry science, often because they believe that they do not have the content knowledge or pedagogical skills to do so. This is a …

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Gillies, R. M., & Nichols, K. (2015). How to support primary teachers’ implementation of inquiry: Teachers’ reflections on teaching cooperative inquiry-based science. Research in Science Education, 45(2), 171-191.
Gillies, Robyn M., and Kim Nichols. "How to support primary teachers’ implementation of inquiry: Teachers’ reflections on teaching cooperative inquiry-based science." Research in Science Education 45.2 (2015): 171-191.
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Using a public library makerspace to bring STEM education to low-income youth

STEM and underrepresentation

Nichols S.
GSID: X0mXs1zfzpUJ
S Nichols, T Schuster, M Ball - 2016 - digitalcommons.georgiasouthern …

… underrepresentation of African Americans in STEM careers has a long-standing legacy. The challenges of STEM … likely available to advocate for their STEM learning. The University of …

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Nichols, S., Schuster, T., & Ball, M. (2016). Using a public library makerspace to bring STEM education to low-income youth.
Nichols, Sharon, Tricia Schuster, and Marti Ball. "Using a public library makerspace to bring STEM education to low-income youth." (2016).
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Intervention for retention through distance education: A comparison study

education interventions

Nichols M.
GSID: XjPsl-E6bGoJ
M Nichols - 2011 - ako.ac.nz

Executive summary To improve student retention in distance education, Simpson (2003) suggests that institutions analyse their own retention characteristics and „spot the leaks …

Self‐efficacy of first‐generation and non‐first‐generation college students: The relationship with academic performance and college adjustment

first generation college student

Nichols L.
GSID: 5-8XEjzd_VYJ
L Ramos‐Sánchez, L Nichols - Journal of college counseling, 2007 - Wiley Online Library

… -generation (traditional college students) have at least one … first-generation college student is used generally to refer to participants with at least one parent who had completed a college …

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Ramos‐Sánchez, L., & Nichols, L. (2007). Self‐efficacy of first‐generation and non‐first‐generation college students: The relationship with academic performance and college adjustment. Journal of college counseling, 10(1), 6-18.
Ramos‐Sánchez, Lucila, and Laura Nichols. "Self‐efficacy of first‐generation and non‐first‐generation college students: The relationship with academic performance and college adjustment." Journal of college counseling 10.1 (2007): 6-18.
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Student perceptions of support services and the influence of targeted interventions on retention in distance education

education interventions

Nichols M.
GSID: zW7OhTd0z2UJ
M Nichols - Distance education, 2010 - Taylor & Francis

To improve student retention in distance education, Simpson suggested in 2003 that institutions analyse their own retention characteristics and ‘spot the leaks.’ In 2008 the Centre for Distance Learning at Laidlaw College, New Zealand, employed two part‐time academic …

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Nichols, M. (2010). Student perceptions of support services and the influence of targeted interventions on retention in distance education. Distance education, 31(1), 93-113.
Nichols, Mark. "Student perceptions of support services and the influence of targeted interventions on retention in distance education." Distance education 31.1 (2010): 93-113.
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Leadership styles and substance.

Stat

Nichols B.
PMID: 5208318
Stat. 1971 May;40(5):19-20.

No abstract available.

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Nichols B. Leadership styles and substance. Stat. 1971;40(5):19-20
Nichols, B. (1971). Leadership styles and substance. Stat, 40(5), 19-20.
Nichols, B. "Leadership styles and substance." Stat vol. 40,5 (1971): 19-20.
Nichols B. Leadership styles and substance. Stat. 1971 May;40(5):19-20. PMID: 5208318.
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Quality control of next-generation sequencing data without a reference.

Frontiers in genetics

Trivedi UH, Cézard T, Bridgett S, Montazam A, Nichols J, Blaxter M, Gharbi K.
PMID: 24834071
Front Genet. 2014 May 06;5:111. doi: 10.3389/fgene.2014.00111. eCollection 2014.

Next-generation sequencing (NGS) technologies have dramatically expanded the breadth of genomics. Genome-scale data, once restricted to a small number of biomedical model organisms, can now be generated for virtually any species at remarkable speed and low cost. Yet non-model...

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Trivedi UH, Cézard T, Bridgett S, et al. Quality control of next-generation sequencing data without a reference. Front Genet. 2014;5:111doi: 10.3389/fgene.2014.00111.
Trivedi, U. H., Cézard, T., Bridgett, S., Montazam, A., Nichols, J., Blaxter, M., & Gharbi, K. (2014). Quality control of next-generation sequencing data without a reference. Frontiers in genetics, 5111. https://doi.org/10.3389/fgene.2014.00111
Trivedi, Urmi H, et al. "Quality control of next-generation sequencing data without a reference." Frontiers in genetics vol. 5 (2014): 111. doi: https://doi.org/10.3389/fgene.2014.00111
Trivedi UH, Cézard T, Bridgett S, Montazam A, Nichols J, Blaxter M, Gharbi K. Quality control of next-generation sequencing data without a reference. Front Genet. 2014 May 06;5:111. doi: 10.3389/fgene.2014.00111. eCollection 2014. PMID: 24834071; PMCID: PMC4018527.
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Personalized Medication Response Prediction for Attention-Deficit Hyperactivity Disorder: Learning in the Model Space vs. Learning in the Data Space.

Frontiers in physiology

Wong HK, Tiffin PA, Chappell MJ, Nichols TE, Welsh PR, Doyle OM, Lopez-Kolkovska BC, Inglis SK, Coghill D, Shen Y, Tiño P.
PMID: 28443027
Front Physiol. 2017 Apr 11;8:199. doi: 10.3389/fphys.2017.00199. eCollection 2017.

Attention-Deficit Hyperactive Disorder (ADHD) is one of the most common mental health disorders amongst school-aged children with an estimated prevalence of 5% in the global population (American Psychiatric Association, 2013). Stimulants, particularly methylphenidate (MPH), are the first-line option in...

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Wong HK, Tiffin PA, Chappell MJ, et al. Personalized Medication Response Prediction for Attention-Deficit Hyperactivity Disorder: Learning in the Model Space vs. Learning in the Data Space. Front Physiol. 2017;8:199doi: 10.3389/fphys.2017.00199.
Wong, H. K., Tiffin, P. A., Chappell, M. J., Nichols, T. E., Welsh, P. R., Doyle, O. M., Lopez-Kolkovska, B. C., Inglis, S. K., Coghill, D., Shen, Y., & Tiño, P. (2017). Personalized Medication Response Prediction for Attention-Deficit Hyperactivity Disorder: Learning in the Model Space vs. Learning in the Data Space. Frontiers in physiology, 8199. https://doi.org/10.3389/fphys.2017.00199
Wong, Hin K, et al. "Personalized Medication Response Prediction for Attention-Deficit Hyperactivity Disorder: Learning in the Model Space vs. Learning in the Data Space." Frontiers in physiology vol. 8 (2017): 199. doi: https://doi.org/10.3389/fphys.2017.00199
Wong HK, Tiffin PA, Chappell MJ, Nichols TE, Welsh PR, Doyle OM, Lopez-Kolkovska BC, Inglis SK, Coghill D, Shen Y, Tiño P. Personalized Medication Response Prediction for Attention-Deficit Hyperactivity Disorder: Learning in the Model Space vs. Learning in the Data Space. Front Physiol. 2017 Apr 11;8:199. doi: 10.3389/fphys.2017.00199. eCollection 2017. PMID: 28443027; PMCID: PMC5387107.
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Conducting LaAlO3/SrTiO3 heterointerfaces on atomically-flat substrates prepared by deionized-water.

Scientific reports

Connell JG, Nichols J, Gruenewald JH, Kim DW, Seo SS.
PMID: 27033248
Sci Rep. 2016 Apr 01;6:23621. doi: 10.1038/srep23621.

We have investigated how the recently-developed water-leaching method for atomically-flat SrTiO3 (STO) substrates affects the transport properties of LaAlO3 (LAO) and STO heterointerfaces. Using pulsed laser deposition at identical growth conditions, we have synthesized epitaxial LAO thin-films on two...

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Connell JG, Nichols J, Gruenewald JH, et al. Conducting LaAlO3/SrTiO3 heterointerfaces on atomically-flat substrates prepared by deionized-water. Sci Rep. 2016;6:23621doi: 10.1038/srep23621.
Connell, J. G., Nichols, J., Gruenewald, J. H., Kim, D. W., & Seo, S. S. (2016). Conducting LaAlO3/SrTiO3 heterointerfaces on atomically-flat substrates prepared by deionized-water. Scientific reports, 623621. https://doi.org/10.1038/srep23621
Connell, J G, et al. "Conducting LaAlO3/SrTiO3 heterointerfaces on atomically-flat substrates prepared by deionized-water." Scientific reports vol. 6 (2016): 23621. doi: https://doi.org/10.1038/srep23621
Connell JG, Nichols J, Gruenewald JH, Kim DW, Seo SS. Conducting LaAlO3/SrTiO3 heterointerfaces on atomically-flat substrates prepared by deionized-water. Sci Rep. 2016 Apr 01;6:23621. doi: 10.1038/srep23621. PMID: 27033248; PMCID: PMC4817030.
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Reply to Brown and Behrmann, Cox, et al., and Kessler et al.: Data and code sharing is the way forward for fMRI.

Proceedings of the National Academy of Sciences of the United States of America

Eklund A, Nichols TE, Knutsson H.
PMID: 28420795
Proc Natl Acad Sci U S A. 2017 Apr 25;114(17):E3374-E3375. doi: 10.1073/pnas.1620285114. Epub 2017 Apr 18.

No abstract available.

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Eklund A, Nichols TE, Knutsson H. Reply to Brown and Behrmann, Cox, et al., and Kessler et al.: Data and code sharing is the way forward for fMRI. Proc Natl Acad Sci U S A. 2017;114(17):E3374-E3375doi: 10.1073/pnas.1620285114.
Eklund, A., Nichols, T. E., & Knutsson, H. (2017). Reply to Brown and Behrmann, Cox, et al., and Kessler et al.: Data and code sharing is the way forward for fMRI. Proceedings of the National Academy of Sciences of the United States of America, 114(17), E3374-E3375. https://doi.org/10.1073/pnas.1620285114
Eklund, Anders, et al. "Reply to Brown and Behrmann, Cox, et al., and Kessler et al.: Data and code sharing is the way forward for fMRI." Proceedings of the National Academy of Sciences of the United States of America vol. 114,17 (2017): E3374-E3375. doi: https://doi.org/10.1073/pnas.1620285114
Eklund A, Nichols TE, Knutsson H. Reply to Brown and Behrmann, Cox, et al., and Kessler et al.: Data and code sharing is the way forward for fMRI. Proc Natl Acad Sci U S A. 2017 Apr 25;114(17):E3374-E3375. doi: 10.1073/pnas.1620285114. Epub 2017 Apr 18. PMID: 28420795; PMCID: PMC5410782.
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Youthful Processing Speed in Older Adults: Genetic, Biological, and Behavioral Predictors of Cognitive Processing Speed Trajectories in Aging.

Frontiers in aging neuroscience

Bott NT, Bettcher BM, Yokoyama JS, Frazier DT, Wynn M, Karydas A, Yaffe K, Kramer JH.
PMID: 28344553
Front Aging Neurosci. 2017 Mar 10;9:55. doi: 10.3389/fnagi.2017.00055. eCollection 2017.

No abstract available.

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Bott NT, Bettcher BM, Yokoyama JS, et al. Youthful Processing Speed in Older Adults: Genetic, Biological, and Behavioral Predictors of Cognitive Processing Speed Trajectories in Aging. Front Aging Neurosci. 2017;9:55doi: 10.3389/fnagi.2017.00055.
Bott, N. T., Bettcher, B. M., Yokoyama, J. S., Frazier, D. T., Wynn, M., Karydas, A., Yaffe, K., & Kramer, J. H. (2017). Youthful Processing Speed in Older Adults: Genetic, Biological, and Behavioral Predictors of Cognitive Processing Speed Trajectories in Aging. Frontiers in aging neuroscience, 955. https://doi.org/10.3389/fnagi.2017.00055
Bott, Nicholas T, et al. "Youthful Processing Speed in Older Adults: Genetic, Biological, and Behavioral Predictors of Cognitive Processing Speed Trajectories in Aging." Frontiers in aging neuroscience vol. 9 (2017): 55. doi: https://doi.org/10.3389/fnagi.2017.00055
Bott NT, Bettcher BM, Yokoyama JS, Frazier DT, Wynn M, Karydas A, Yaffe K, Kramer JH. Youthful Processing Speed in Older Adults: Genetic, Biological, and Behavioral Predictors of Cognitive Processing Speed Trajectories in Aging. Front Aging Neurosci. 2017 Mar 10;9:55. doi: 10.3389/fnagi.2017.00055. eCollection 2017. PMID: 28344553; PMCID: PMC5344896.
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The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

Scientific data

Gorgolewski KJ, Auer T, Calhoun VD, Craddock RC, Das S, Duff EP, Flandin G, Ghosh SS, Glatard T, Halchenko YO, Handwerker DA, Hanke M, Keator D, Li X, Michael Z, Maumet C, Nichols BN, Nichols TE, Pellman J, Poline JB, Rokem A, Schaefer G, Sochat V, Triplett W, Turner JA, Varoquaux G, Poldrack RA.
PMID: 27326542
Sci Data. 2016 Jun 21;3:160044. doi: 10.1038/sdata.2016.44.

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain....

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Gorgolewski KJ, Auer T, Calhoun VD, et al. The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Sci Data. 2016;3:160044doi: 10.1038/sdata.2016.44.
Gorgolewski, K. J., Auer, T., Calhoun, V. D., Craddock, R. C., Das, S., Duff, E. P., Flandin, G., Ghosh, S. S., Glatard, T., Halchenko, Y. O., Handwerker, D. A., Hanke, M., Keator, D., Li, X., Michael, Z., Maumet, C., Nichols, B. N., Nichols, T. E., Pellman, J., Poline, J. B., Rokem, A., Schaefer, G., Sochat, V., Triplett, W., Turner, J. A., Varoquaux, G., & Poldrack, R. A. (2016). The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Scientific data, 3160044. https://doi.org/10.1038/sdata.2016.44
Gorgolewski, Krzysztof J, et al. "The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments." Scientific data vol. 3 (2016): 160044. doi: https://doi.org/10.1038/sdata.2016.44
Gorgolewski KJ, Auer T, Calhoun VD, Craddock RC, Das S, Duff EP, Flandin G, Ghosh SS, Glatard T, Halchenko YO, Handwerker DA, Hanke M, Keator D, Li X, Michael Z, Maumet C, Nichols BN, Nichols TE, Pellman J, Poline JB, Rokem A, Schaefer G, Sochat V, Triplett W, Turner JA, Varoquaux G, Poldrack RA. The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Sci Data. 2016 Jun 21;3:160044. doi: 10.1038/sdata.2016.44. PMID: 27326542; PMCID: PMC4978148.
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Showing 1 to 12 of 1142 entries