Can the use of Google Colab improve female and male mathematical analytical thinking in biomedical engineering students?

Google Colab is a free product from Google Research, which allows programming in Python from a browser, and is primarily suitable for (1) machine learning, (2) data analysis, and (3) education. Google Colab is an online programming environment that requires no installation. It has basic math (Math), deep learning (TensorFlow), machine learning (Scikit-learn) and graphing (Matplotlib) tools. Like other Google online tools, it has collaborative properties that allow parallel programming by different users, whose work environments are stored in Google Drive. In addition, it is possible to document the codes with multimedia material, and to publish and import from GitHub.

Therefore, this project aims to use Google Colab as an assistance teaching tool that takes into account the interests and competencies of male and female biomedical engineering students to improve their experience and academic performance. The project proposes to use Google Colab in three ways: (1) implementing study cases in the health area with illustrative materials (e.g., images, sounds, web pages), (2) continuous monitoring by the teacher, and (3) asynchronous collaborative programming. For this purpose, a teacher's guide and a repository of example activities will be implemented in accordance with student feedback.

The project seeks to develop mathematical analytical thinking to quantitatively interpret measurements of biological systems. On the one hand, male students are expected to increase their interest in mathematical analysis through computational development (characteristic more preferred by men). On the other hand, female students are expected to have online mathematical counseling and study cases in the health area (characteristics more preferred by women).

The overall goal is to change the dynamics of teaching applied mathematics, which is an important factor of withdraw, mainly of women in engineering. Men and women have different interests and competencies in engineering, and the frequent ignoring of this fact in the teaching process could be a factor in the current gender gap in STEM (Science, Tech, Engineering and Math).

This proposal is scalable because Google Colab is a free, friendly and executable programming environment in the cloud. It does not involve economic, administrative or infrastructural costs. It is also transferable not only for other blocks and subjects of biomedical engineering, but also for any other engineering, where programming tools are indispensable. Google Colab is a simple and easy to learn environment.

谷歌 Colab 是谷歌研究院推出的免费产品，它允许用户通过浏览器进行 Python 编程，主要适用于（1）机器学习，（2）数据分析以及（3）教育领域。谷歌 Colab 是一款无需安装的在线编程环境，它配备了基础的数学（Math）、深度学习（TensorFlow）、机器学习（Scikit-learn）以及绘图（Matplotlib）工具。如同其他谷歌在线工具，它具备协作特性，允许多用户并行编程，且用户的工作环境存储于谷歌 Drive 中。此外，它还支持使用多媒体素材对代码进行文档记录，以及从 GitHub 导入和发布。因此，本项目的目标在于将谷歌 Colab 作为辅助教学工具，充分考虑男性和女性生物医学工程学生的兴趣和技能，以提升他们的学习体验和学术成绩。项目计划以三种方式使用谷歌 Colab：（1）实施带有说明性材料的健康领域案例研究（例如，图像、声音、网页），（2）教师的持续监控，以及（3）异步协作编程。为此，将根据学生反馈实施教师指导手册和示例活动库。项目旨在培养数学分析思维能力，以定量解读生物系统测量数据。一方面，期望男性学生通过计算发展（男性更偏好的特征）提高对数学分析的兴趣。另一方面，期望女性学生通过在线数学辅导和健康领域的案例研究（女性更偏好的特征）获得帮助。总体目标是改变应用数学教学的动态，这是女性在工程领域退学的一个重要因素。男性和女性在工程领域拥有不同的兴趣和技能，而教学过程中忽视这一事实可能是当前 STEM（科学、技术、工程和数学）领域性别差距的一个因素。本提案具有可扩展性，因为谷歌 Colab 是一个免费、友好且易于执行的云端编程环境，它不涉及经济、行政或基础设施成本。它还适用于其他生物医学工程领域和任何需要编程工具的工程领域。谷歌 Colab 是一个简单且易于学习的环境。