INTERACTIVE LEARNING AND ANALYTICS PLATFORM
Systems and methods, and non-transitory computer-readable medium storing instructions that, when executed, causes a processor to perform operations, including displaying a storyboard via a user output device. The story board may include a plurality of frames. The frames may include an illustration. The illustration may include a first state and a second state. The operations may further include changing the illustration within the frame from the first state to the second state based on a scroll command from a user input device from a first frame to a second frame of the plurality of frames.
This application claims the benefit of priority provisional U.S. Application No. 63/142,897, filed Jan. 28, 2021, which is incorporated herein by reference in its entirety. Further, this application is related to U.S. Design patent application Serial No. 29/768,319 (U031-0002US), filed on Jan. 28, 2021, the disclosure of which is incorporated by reference herein.
TECHNICAL FIELDThe present disclosure relates generally to systems and methods for providing an educational platform. Specifically, the present disclosure relates to systems and methods for providing an interactive educational platform that improves teaching and immersive learning through a highly interactive and analytics education platform.
BACKGROUNDProviding education to individuals of all ages is ubiquitous throughout the world. Educators often rely on textbooks, visual presentations, interactive (e.g., hands on) learning, and computer-drive educational tools to assist in teaching and learning. However, many of these educational tools lack the ability for students and educators the ability to share ideas and progress through a curriculum in a timely manner while still providing immersive interaction between students and educators.
Further, in many instances, students are unable to discuss topics or learning objectives with an educator (e.g., a teacher or professor) since the presentation of information by the educator may continue without the educator knowing that a student needs to have a question answered or clarification provided. Still further, in online learning situations where the information is being presented over a computer network, students may not be able to communicate in a meaningful way during presentation of the topic or learning objectives.
Still further, in some instances, educators are unable to provide meaningful feedback on a student's performance in a timely manner. Often, students may desire to know how well they are understanding the topic or learning objectives and what may be done to improve in the course of study. Further, teachers and professors may similarly not realize how well their students are performing and understanding the topic and learning objectives and how the teachers and professors may assist an individual or group of students to improve. Because some topics and learning objectives build on one another through a course of learning, it may be difficult to identify where a student's understanding is lacking and when to intervene with additional clarification and learning.
The detailed description is set forth below with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different figures indicates similar or identical items. The systems depicted in the accompanying figures are not to scale and components within the figures may be depicted not to scale with each other.
The present systems and methods provide interaction of text and visuals during a learning instance by allowing a student and/or educator to scroll through a presentation that includes one or more learning topics and allow for an immersive interaction between the student and the educator. Further, the manner in which the learning interactions occur may be identified, stored, and analyzed in order to provide the student and/or the educator with knowledge as to how well the information presented as the learning objective is being received and understood. These analytics may assist a student by allowing the student to identify concepts that may have not been fully understood as well as concepts that are understood. Further, these analytics may assist the educator in identifying a level of understanding of the curriculum as a whole and/or individual concepts within the curriculum for an individual student and/or a plurality of students (e.g., a classroom of students).
Examples described herein provide a non-transitory computer-readable medium storing instructions that, when executed, causes a processor to perform operations, including displaying a storyboard via a user output device. The story board may include a plurality of frames. The frames may include an illustration. The illustration may include a first state and a second state. The operations may further include changing the illustration within the frame from the first state to the second state based on a scroll command from a user input device from a first frame to a second frame of the plurality of frames.
The operations may further include transmitting a user query. The user query may include an identification of a position within the storyboard the user query was created. The operations may further include presenting the position within the storyboard the user query was created in response to a request to access to the user query and transmitting a response to the user query in response to user input.
The operations may further include storing user query data, determining a plurality of variables associated with user interaction with the frames, and determining analytic data based on the variables, the analytic data defining a level of interaction with the frames. The operations may further include generating a report based on the analytic data.
The report based on the analytic data may include information defining a level of effort by a student, a level of comprehension of the student, effort trends by the student, a learning objective the student should focus on based on a number of likes associated with the learning objective, a learning objective the student should focus on based on performance of the student as to the leaning objective, or combinations thereof. Further, the report based on the analytic data may include information defining a number of questions presented by the student, a number of annotations to the storyboard by the student, a ranking of learning objectives most misunderstood by the student, a ranking of which questions are most misunderstood by the student, a ranking of which learning objectives are associated with the most questions, a ranking of students that require support based on performance, or combinations thereof.
The analytic data may define interactions with at least one question presented at the frames, and the operations may further include generating the report based on the analytic data includes a review sheet of the frames specific to a first interactions with the frames from a first client device. Further, the analytic data may define interactions with at least one question presented at the frames, and the operations may further include generating the report based on the analytic data includes a ranking of the interactions with the at least one question.
Examples described herein also provide a method including displaying a storyboard via a user output device. The story board may include a plurality of frames. The frames may include an illustration, the illustration including a first state and a second state. The method may further include changing the illustration within the frame from the first state to the second state based on a scroll command from a user input device from a first frame to a second frame of the plurality of frames.
The method may further include transmitting a user query. The user query may include an identification of a position within the storyboard the user query was created. The method may further include presenting the position within the storyboard the user query was created in response to a request to access to the user query and transmitting a response to the user query in response to user input.
The method may further include storing user query data, determining a plurality of variables associated with user interaction with the frames, and determining analytic data based on the variables, the analytic data defining a level of interaction with the frames.
The method may further include generating a report based on the analytic data. The report may be based on the analytic data includes information defining a level of effort by a student, a level of comprehension of the student, effort trends by the student, a learning objective the student should focus on based on a number of likes associated with the learning objective, a learning objective the student should focus on based on performance of the student as to the leaning objective, or combinations thereof. The method may further include generating a report based on the analytic data. The report may be based on the analytic data includes information defining a number of questions presented by the student, a number of annotations to the storyboard by the student, a ranking of learning objectives most misunderstood by the student, a ranking of which questions are most misunderstood by the student, a ranking of which learning objectives are associated with the most questions, a ranking of students that require support based on performance, or combinations thereof.
The analytic data may define interactions with at least one question presented at the frames, and the method may further include generating the report based on the analytic data includes a review sheet of the frames specific to a first interactions with the frames from a first client device. The analytic data defines interactions with at least one question presented at the frames, and the method may further include generating the report based on the analytic data includes a ranking of the interactions with the at least one question.
Examples described herein also provide a system including a processor, and a non-transitory computer-readable media storing instructions that, when executed by the processor, causes the processor to perform operations including displaying a storyboard via a user output device. The story board may include a plurality of frames, the frames including an illustration, the illustration including a first state and a second state. The operations may further include changing the illustration within the frame from the first state to the second state based on a scroll command from a user input device from a first frame to a second frame of the plurality of frames, transmitting a user query, the user query including an identification of a position within the storyboard the user query was created, presenting the position within the storyboard the user query was created in response to a request to access to the user query, and transmitting a response to the user query in response to user input.
The operations may further include transmitting a user query, the user query including an identification of a position within the storyboard the user query was created, presenting the position within the storyboard the user query was created in response to a request to access to the user query, and transmitting a response to the user query in response to user input. The operations may further include storing user query data, determining a plurality of variables associated with user interaction with the frames, and determining analytic data based on the variables, the analytic data defining a level of interaction with the frames. The operations may further include generating a report based on the analytic data.
Additionally, the techniques described in this disclosure may be performed as a method and/or by a system having non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, performs the techniques described above.
EXAMPLE EMBODIMENTSTurning now to the figures,
The frames may include a number of different types of content that may define the type of frame included. These types of frames include, for example, a frame including text, a definition frame including definitions of terms included in the presentation, a quote frame including quotes pertinent to the presentation, an expandable portions such as dropdown menus to select form that cause the frame to change, a table, question portions such as, for example, multiple choice, number, and free response questions, and combinations of the above. In this manner, any type of non-interactive and/or interactive text may be presented within the frames.
The presentation may also include a number of visualizations. The visualizations may appear in the format of a canvas. A canvas may be any container that holds various drawing elements (lines, shapes, text, frames containing other elements, etc.), in some examples, arranges the logical representation of a user interface or graphical scene, and may define the spatial representation and allow the user to interact with the elements via a graphical user interface. In one example, each canvas displayed within the visualization may have unique components, and each component within the canvas may have unique attributes.
Some types of canvases may include, for example, a graph, a flowchart, and a chart, among a myriad of other types of visual elements. A graph within the canvas may include a number of components including, for example, a line (including colors, functions, etc.), a point, a label, an area, and a tangent, among a myriad of other components. A flowchart within the canvas may include node components, and edge components, among a myriad of other components. A chart within the canvas may include a pie chart including colors, sizes of portions of the pie chart, and values (in terms of a percentage out of 100), among a myriad of other components presentable within a pie chart. A chart within the canvas may also include a line chart including colors, sizes, and values, among a myriad of other components presentable within a line chart.
Interaction with the frames such as movement through the number of frames may cause a number of attributes of the components within the visualizations to animate. For example, when a frame comes into view, the presentation may cause the visualization to animate including altering the attributes of the components within the canvas resulting in a number of animations within the canvas of the visualization. This animation keeps a student engaged in the presentation and assist in further understanding of the topic of study. Any type and amount of animation may be provided within the presentation.
The presentation may also include a number of user-interactive elements that the presenter (e.g., educator, professor, teacher, etc.) and/or the participant (e.g., the student, user, etc.) may interact with.
Each frame within the presentation may include text. The text within the frames may be selected by a user via a user-selection device such as a mouse. In one example, selection of the text within the frame(s) allows a participant to ask a question associated with the selected text, highlight or mark the selected text, and annotate the selected text by adding comments or other notes to the text inline or within out-of-line comment balloons, among other actions associated with the selected text. Each annotation and/or highlight may be anchored to the location of the frame in the page such that when the user selects the link for the annotation, the storyboard will scroll down to the location of the frame in which the annotation is anchored and was originally marked.
The presenter (e.g., educator, professor, teacher, etc.) may also be provided a view of the presentation. The presenter view makes the frames and/or the text within the frames larger for viewing by the participants. Further, the presenter view may cause the visualizations to become larger as well for viewing by the participants. Still further, the presenter view may add a number of annotation tools described above. The presenter may make any changes to the presentation before or during the display of the presentation. For example, the presenter may alter the sizes of frames and visualizations in the presentation.
As the presenter presents the presentation to the participants (e.g., in a streaming scenario), the presenter's actions may be synchronized to the participants' screens. For example, a position of the presenter's pointer as input by the presenter's mouse device may cause a laser pointer simulation to appear at a corresponding location on the participants' screens as the participants view the streamed content.
In one example, the participants may scroll through the various frames within the presentation without affecting the presenter's version within the presenter view. As the participant does this, a “return to live view” button may appear to allow the participant to return to the live lecture at the point within the presentation at which the presenter is currently lecturing from. In this manner, the participant may freely access and view past and future frames separate from the frame the presenter is currently discussing and displaying but may still move back to the portion of the presentation the presenter is currently discussing (e.g., lecturing on).
As the presenter is lecturing, the participant may use any number of annotation tools (e.g., arrows, highlighting, points, pens, etc.) to annotate the presentation. As the participant annotates the presentation, a copy of the presentation may be saved to the participant's computing device so that the participant may retain their annotations. This may assist the participant in retaining any notes from the lecture for later study.
In one example, the system may track the participant's mouse positions and the annotation tools they are using. For example, a position of the participant's mouse, a scroll position, an annotation tool, a type of annotation, and a first selection using a mouse and a second selection using a mouse, among other participant interactions may be tracked live.
Further, the participants may ask questions in a real-time manner during the presentation. The questions may include, for example, an informal reaction to the presenter's lecture including presentation of a thumbs up, thumbs down, smiley face, frowned face, etc. as a reaction to the presenter's lecture. Further, the questions may include, for example, a chat session where a question is asked over text or voice by the participant and/or the presenter. For example, a presenter may ask a question and verbally to textually prompt the participant to type or speak the answer via a chat session incorporated into the presentation. The questions may further include, for example, formal questions where the questions are presented in frames. The answers to any of these types of questions may be received by the presented in real-time to allow the presenter to identify whether the topic being discussed is being understood/appreciated by the participants.
In the example of
Turning again to
More specifically,
As mentioned above, participants such as students and educators such as teachers or professors may desire to interact with one another both during the presentation (e.g., during a lecture or class) and outside of the class or lecture.
In the example of
Any type of communication may be utilized to inform the presenter of the query from the student including email, short message service (SMS) (e.g., in the form of texts and/or chat communications), instant messaging, communication via social media platforms, among a myriad of other types of communication.
With the present systems and methods, a number of data may be procured, processed, and provided to the educator and/or the students to provide direction as to the effectiveness of the presentation. As mentioned above, a myriad of analytics data may be obtained during the participant's interaction with the presentation. The analytics data may be obtained during a live presentation by the presenter and/or during an offline instance where the participant is reviewing or studying the material within the presentation during a time when the presenter is not presenting the presentation. A computing device associated with the execution of computer readable code of the presentation or any other computing device capable of tracking user-interactions with the presentation may obtain a number of analytics data. The analytics data may be used, in turn, to determine the effectiveness of the presentation as to the understanding of the topic(s) taught via the presentation. Further, the analytics data may be used to identify specific topics or subtopics the participant may or may not have fully understood. Knowing this data allows for better presentations to be prepared in the future and for participants and/or presenters to assist in the learning of the topics and subtopics.
The types of knowledge-based elements of the presentation may include, for example, a course, a semester, a trimester, a term, a class, a lecture, a topic, a subtopic, learning objectives, and individual frames, among other types of knowledge-based elements of the presentation. Learning objectives may be defined as any number of frames grouped together to teach a topic, subtopic, and/or concept. A learning objective may be classified as a prerequisite of a second learning objective.
The inputs and/or interactions of participants (e.g., students, etc.) and the presenter (e.g., professor, teacher, TA, etc.) may be tracked, identified, and stored as analytics data. Thus, the associated computing device may include a data storage device such as analytics database.
As to participant inputs, a degree of effort spent learning from the presentation may be tracked, identified, and stored as the analytics data. The number of sessions spent by the participant, the time spent in each session, an average duration of each session, time between sessions, time spent at each frame of the presentation (which may indicate a level of understanding of the topic or an indication of failed understanding due to a relatively shorter duration of time spent at one or more frames), idle versus engaged time tracking based on user inputs detected within the frames, time spent within a learning objective, notes taken in the frames, questions asked and answered by the participant, exam or test performance, among a myriad of different metrics that may be obtained from the participant's inputs.
The metrics may include metrics defining effort spent learning. Effort spent learning may be measured by a number of metrics including, for example, the number of sessions the participant participates in. The sessions may be broadly defined as any separate and individual instances of interaction with the presentation. In one example, a session may include an entirety of a lecture or a portion thereof. A total amount of time spent during each session as well as an average time spent for a plurality of sessions may be included as metrics. Further, time spent between sessions may also be included as metrics for the analytics data.
Idle time and engaged time of the user may be tracked as analytics data to determine time spent by the user within a session. Idle time tracking tracks the user's time for when they are on a page but nothing has moved (scroll position or mouse position, for more than a first predetermined duration of time (e.g., 3 minutes)). Engaged time is when the mouse/scroll position has changed at least once within a second predetermined duration of time (e.g., within the past 60 seconds). When the scroll/mouse position has not changed within the second predetermined duration of time (e.g., with the last 60 seconds), but has not been more than the first predetermined duration (e.g., within 3 minutes), the user's level of engagement may not be determined or determinable.
Another metric that defines the analytics data may include time spent with a learning objective. In one example, the time spent with a learning objective may be a cumulative duration of time spent on a number of frames associated with the learning objective. In one example, the time spent with a learning objective may include time spent on each frame over a period of time.
Student inputs used as analytics data may also include note taking. The executable code described herein allows for the user to take notes using a number of different types of note taking within the text of the frame, and may include, for example, a number of words highlighted, a number of annotations/highlights made, a number of tags created in association with the text of the frames, other forms of note taking, and combinations thereof. These annotations may also be collected and identified as analytic data.
Student inputs used as analytics data may also include questions presented and answered by users. For example, the number of questions asked by the user may form part of the analytics. As to the questions asked by the user, the numbers of “likes” given for the question and the number of questions solved and unsolved may also be used as analytics data. Further, the number of questions the user replies to, likes, and/or replied to and solved may also serve as analytics data.
Student inputs used as analytics data may also include practice activities preformed by the user. For each question presented to the user, the analytics data may include data defining whether the user attempted the question(s), whether the user answered the question correctly on a first attempt, time spent on the question(s) overall, time taken by the user before they obtain a correct solution, and the number of attempts before obtaining a correct solution, and other metrics associated with the questions. The analytics data may also include whether other individuals (e.g., other students, etc.) offer feedback appertaining to the practice activities. For each question, the analytics data may include which of the learning objectives are most problematic for each question, and which questions the user finds difficult. Further, for each practice activity, it may be determined whether the user has a firm grip over the learning objectives of the practice activity.
Still further, based on each practice question, the aggregate of correctly answered questions plus the average for the entire practice may be considered. In this example, the time spent on the entire practice, the percent of questions attempted, the percent of questions correctly answered on the first try, time spent before looking at the solution, and/or number of attempts before looking at the solution may be considered.
Student inputs used as analytics data may also include exam performance by the user. The analytics data may include, for example, how many sessions and/or time spent on practicing before an exam, an average grade for each learning objective, and an average grade for the entire exam, among other exam performance related metrics.
Presenter inputs (e.g., inputs from a professor, a teacher's assistant (TA), etc.) may also be provided using the present systems and methods. As to participants' efforts identified by the presents systems and methods and provided to the presenter may include, for example, highlighted words, a number of questions answered, time spent on grading, time spent on making courses, time spent on answering questions/chats, and other metrics.
Student feedback to the professor may also be included as presenter inputs. The student feedback may include a number of students who find the class difficult, a number of students who would take the course again and/or recommend the course, a difference between grades expected by the participants and an actual grade received (e.g., “What grade do you expect in the class?” and the actual grade received), and additional questions that students can answer at the end of the course or class including the following:
The inputs may also include professor feedback that is to be determined.
Student and Educator InteractionThe educator may prepare the presentation using the present systems and methods and may also edit the presentation as feedback including the analytic data described above is known.
The effort metrics of
Further, the identification of prerequisite learning objectives that may prove difficult for a user may be identified based on performance of the learning objectives. In this example, when a user is displaying difficulty in understanding the learning objectives, it may be as a result of a poor understanding of the prerequisite learning objective(s) including the keystone learning objective(s). Thus, this information may be conveyed to the users including the participant (e.g., the student, etc.) and the presenter (e.g., the professor, teacher, TA, etc.).
The systems and methods described herein may rely on one or more data maps, look-up tables, neural networks, algorithms, machine learning algorithms, and/or other components relating to the operating conditions and the operating environment of the system that may be stored in the memory. Each of the data maps noted above may include a collection of data in the form of tables, graphs, and/or equations to maximize the performance and efficiency of the system and its operation. Machine learning uses algorithms and statistical models to cause the present systems and methods to perform a specific task without continuous explicit instructions input. Here the specific task being learned is the processing of analytics data to obtain the output data and perform the processes described herein. The system may rely on patterns and inferences as to how to process the analytics data. A mathematical model may be built by the system based on training data obtained from, for example, previous instances of analytics data collection and implementation of the present systems and methods. This training data may serve as a basis for the system to determine how to predict or decide to perform the processes and provide the output described herein.
Similarly,
The present systems and methods may be implemented via a number of components of a client device according to an example of the principles described herein. The client device may include one or more hardware processor(s) configured to execute one or more stored instructions. The processor(s) may comprise one or more cores. Further, the client device may include one or more network interfaces configured to provide communications between the client device and other devices, such as devices associated with the system architecture described herein, including, for example, user computing devices, a network, servers, and/or other systems or devices associated with the client device and/or remote from the client device. The network interfaces may include devices configured to couple to personal area networks (PANs), wired and wireless local area networks (LANs), wired and wireless wide area networks (WANs), and so forth. For example, the network interfaces may include devices compatible with the client devices, and/or other systems or devices associated with the client device.
The client device may also include computer-readable media that stores various executable components (e.g., software-based components, firmware-based components, etc.). In one example, the computer-readable media may include, for example, working memory, random access memory (RAM), read only memory (ROM), and other forms of persistent, non-persistent, volatile, non-volatile, and other types of data storage. In addition to various components discussed herein, the computer-readable media 606 may further store components to implement functionality described herein. While not illustrated, the computer-readable media may store one or more operating systems utilized to control the operation of the one or more devices that comprise the client device. According to one example, the operating system comprises the LINUX operating system. According to another example, the operating system(s) comprise the WINDOWS SERVER operating system from MICROSOFT Corporation of Redmond, Wash. According to further examples, the operating system(s) may comprise the UNIX operating system or one of its variants. It may be appreciated that other operating systems may also be utilized.
Additionally, the client device may include a data store which may comprise one, or multiple, repositories or other storage locations for persistently storing and managing collections of data such as databases, simple files, binary, and/or any other data. The data store may include one or more storage locations that may be managed by one or more database management systems. The data store may store, for example, application data defining computer-executable code utilized by the processor to execute the applications. Further, the application data may include data relating to the execution of the methods described herein, the analytics data obtained during the sessions, and other data that may be used by the applications to provide the outputs described herein. The computer-readable media may store portions, or components, of the applications that support the methods described herein.
The server computers 4602 may be standard tower, rack-mount, or blade server computers configured appropriately for providing computing resources. In some examples, the server computers 4602 may provide computing resources 4604 including data processing resources such as VM instances or hardware computing systems, database clusters, computing clusters, storage clusters, data storage resources, database resources, networking resources, virtual private networks (VPNs), and others. Some of the server computers 4602 may also be configured to execute a resource manager 4606 capable of instantiating and/or managing the computing resources. In the case of VM instances, for example, the resource manager 4606 may be a hypervisor or another type of program configured to enable the execution of multiple VM instances on a single server computer 4602. Server computers 4602 in the data center 4600 may also be configured to provide network services and other types of services.
In the example data center 4600 shown in
In some examples, the server computers 4602 and or the computing resources 4604 may each execute/host one or more tenant containers and/or virtual machines to perform techniques described herein.
In some instances, the data center 4600 may provide computing resources, like tenant containers, VM instances, VPN instances, and storage, on a permanent or an as-needed basis. Among other types of functionality, the computing resources provided by a cloud computing network may be utilized to implement the various services and techniques described herein. The computing resources 4604 provided by the cloud computing network may include various types of computing resources, such as data processing resources like tenant containers and VM instances, data storage resources, networking resources, data communication resources, network services, VPN instances, and the like.
Each type of computing resource 4604 provided by the cloud computing network may be general-purpose or may be available in a number of specific configurations. For example, data processing resources may be available as physical computers or VM instances in a number of different configurations. The VM instances may be configured to execute applications, including web servers, application servers, media servers, database servers, some or all of the network services described above, and/or other types of programs. Data storage resources may include file storage devices, block storage devices, and the like. The cloud computing network may also be configured to provide other types of computing resources 4604 not mentioned specifically herein.
The computing resources 4604 provided by a cloud computing network may be enabled in one example by one or more data centers 4600 (which might be referred to herein singularly as “a data center 4600” or in the plural as “the data centers 4600). The data centers 4600 are facilities utilized to house and operate computer systems and associated components. The data centers 4600 typically include redundant and backup power, communications, cooling, and security systems. The data centers 4600 may also be located in geographically disparate locations. One illustrative example for a data center 4600 that may be utilized to implement the technologies disclosed herein is described herein with regard to, for example,
The computer 4700 includes a baseboard 4702, or “motherboard,” which is a printed circuit board to which a multitude of components or devices may be connected by way of a system bus or other electrical communication paths. In one illustrative configuration, one or more central processing units (CPUs) 4704 operate in conjunction with a chipset 4706. The CPUs 4704 may be standard programmable processors that perform arithmetic and logical operations necessary for the operation of the computer 4700.
The CPUs 4704 perform operations by transitioning from one discrete, physical state to the next through the manipulation of switching elements that differentiate between and change these states. Switching elements generally include electronic circuits that maintain one of two binary states, such as flip-flops, and electronic circuits that provide an output state based on the logical combination of the states of one or more other switching elements, such as logic gates. These basic switching elements may be combined to create more complex logic circuits, including registers, adders-subtractors, arithmetic logic units, floating-point units, and the like.
The chipset 4706 provides an interface between the CPUs 4704 and the remainder of the components and devices on the baseboard 4702. The chipset 4706 may provide an interface to a RAM 4708, used as the main memory in the computer 4700. The chipset 4706 may further provide an interface to a computer-readable storage medium such as a read-only memory (ROM) 4710 or non-volatile RAM (NVRAM) for storing basic routines that help to startup the computer 4700 and to transfer information between the various components and devices. The ROM 4710 or NVRAM may also store other software components necessary for the operation of the computer 4700 in accordance with the configurations described herein.
The computer 4700 may operate in a networked environment using logical connections to remote computing devices and computer systems through a network, such as the data center 4600, the server computers 4602, client devices, among other devices. The chipset 4706 may include functionality for providing network connectivity through a Network Interface Controller (NIC) 4712, such as a gigabit Ethernet adapter. The NIC 4712 is capable of connecting the computer 4700 to other computing devices within the data center 4600, the server computers 4602, client devices and external to the data center 4600, the server computers 4602, client devices. It may be appreciated that multiple NICs 4712 may be present in the computer 4700, connecting the computer to other types of networks and remote computer systems. In some examples, the NIC 4712 may be configured to perform at least some of the techniques described herein, such as packet redirects and/or other techniques described herein.
The computer 4700 may be connected to a storage device 4718 that provides non-volatile storage for the computer. The storage device 4718 may store an operating system 4720, programs 4722 (e.g., any computer-readable and/or computer-executable code described herein), and data, which have been described in greater detail herein. The storage device 4718 may be connected to the computer 4700 through a storage controller 4714 connected to the chipset 4706. The storage device 4718 may consist of one or more physical storage units. The storage controller 4714 may interface with the physical storage units through a serial attached SCSI (SAS) interface, a serial advanced technology attachment (SATA) interface, a fiber channel (FC) interface, or other type of interface for physically connecting and transferring data between computers and physical storage units.
The computer 4700 may store data on the storage device 4718 by transforming the physical state of the physical storage units to reflect the information being stored. The specific transformation of physical state may depend on various factors, in different examples of this description. Examples of such factors may include, but are not limited to, the technology used to implement the physical storage units, whether the storage device 4718 is characterized as primary or secondary storage, and the like.
For example, the computer 4700 may store information to the storage device 4718 by issuing instructions through the storage controller 4714 to alter the magnetic characteristics of a particular location within a magnetic disk drive unit, the reflective or refractive characteristics of a particular location in an optical storage unit, or the electrical characteristics of a particular capacitor, transistor, or other discrete component in a solid-state storage unit. Other transformations of physical media are possible without departing from the scope and spirit of the present description, with the foregoing examples provided only to facilitate this description. The computer 4700 may further read information from the storage device 4718 by detecting the physical states or characteristics of one or more particular locations within the physical storage units.
In addition to the storage device 4718 described above, the computer 4700 may have access to other computer-readable storage media to store and retrieve information, such as program modules, data structures, or other data. It may be appreciated by those skilled in the art that computer-readable storage media is any available media that provides for the non-transitory storage of data and that may be accessed by the computer 4700. In some examples, the operations performed by the data center 4600, the server computers 4602, client devices, and or any components included therein, may be supported by one or more devices similar to computer 4700. Stated otherwise, some or all of the operations performed by the data center 4600, the server computers 4602, client devices, and or any components included therein, may be performed by one or more computer devices operating in a cloud-based arrangement.
By way of example, and not limitation, computer-readable storage media may include volatile and non-volatile, removable and non-removable media implemented in any method or technology. Computer-readable storage media includes, but is not limited to, RAM, ROM, erasable programmable ROM (EPROM), electrically-erasable programmable ROM (EEPROM), flash memory or other solid-state memory technology, compact disc ROM (CD-ROM), digital versatile disk (DVD), high definition DVD (HD-DVD), BLU-RAY, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that may be used to store the desired information in a non-transitory fashion.
As mentioned briefly above, the storage device 4718 may store an operating system 4720 utilized to control the operation of the computer 4700. According to one example, the operating system 4720 comprises the LINUX operating system. According to another example, the operating system comprises the WINDOWS® SERVER operating system from MICROSOFT Corporation of Redmond, Wash. According to further examples, the operating system may comprise the UNIX operating system or one of its variants. It may be appreciated that other operating systems may also be utilized. The storage device 4718 may store other system or application programs and data utilized by the computer 4700.
In one example, the storage device 4718 or other computer-readable storage media is encoded with computer-executable instructions which, when loaded into the computer 4700, transform the computer from a general-purpose computing system into a special-purpose computer capable of implementing the examples described herein. These computer-executable instructions transform the computer 4700 by specifying how the CPUs 4704 transition between states, as described above. According to one example, the computer 4700 has access to computer-readable storage media storing computer-executable instructions which, when executed by the computer 4700, perform the various processes described above with regard to
The computer 4700 may also include one or more input/output controllers 4716 for receiving and processing input from a number of input devices, such as a keyboard, a mouse, a touchpad, a touch screen, an electronic stylus, or other type of input device. Similarly, an input/output controller 4716 may provide output to a display, such as a computer monitor, a flat-panel display, a digital projector, a printer, or other type of output device. It will be appreciated that the computer 4700 might not include all of the components shown in
As described herein, the computer 4700 may comprise one or more of the data center 4600, the server computers 4602, client devices, and/or other systems or devices associated with the data center 4600, the server computers 4602, client devices and/or remote from the data center 4600, the server computers 4602, client devices. The computer 4700 may include one or more hardware processor(s) such as the CPUs 4704 configured to execute one or more stored instructions. The CPUs 4704 may comprise one or more cores. Further, the computer 4700 may include one or more network interfaces configured to provide communications between the computer 4700 and other devices, such as the communications described herein as being performed by the data center 4600, the server computers 4602, client devices, and other devices described herein. The network interfaces may include devices configured to couple to personal area networks (PANs), wired and wireless local area networks (LANs), wired and wireless wide area networks (WANs), and so forth. For example, the network interfaces may include devices compatible with Ethernet, Wi-Fi™, and so forth.
The programs 4722 may comprise any type of programs or processes to perform the techniques described in this disclosure for the data center 4600, the server computers 4602, client devices as described herein. The programs 4722 may enable the devices described herein to perform various operations.
CONCLUSIONWhile the present systems and methods are described with respect to the specific examples, it is to be understood that the scope of the present systems and methods are not limited to these specific examples. Since other modifications and changes varied to fit particular operating requirements and environments will be apparent to those skilled in the art, the present systems and methods are not considered limited to the example chosen for purposes of disclosure, and covers all changes and modifications which do not constitute departures from the true spirit and scope of the present systems and methods.
Although the application describes examples having specific structural features and/or methodological acts, it is to be understood that the claims are not necessarily limited to the specific features or acts described. Rather, the specific features and acts are merely illustrative some examples that fall within the scope of the claims of the application.
Claims
1. A non-transitory computer-readable medium storing instructions that, when executed, causes a processor to perform operations, comprising:
- displaying a storyboard via a user output device, the story board comprising: a plurality of frames, the frames comprising an illustration, the illustration comprising a first state and a second state; and
- changing the illustration within the frame from the first state to the second state based on a scroll command from a user input device from a first frame to a second frame of the plurality of frames.
2. The non-transitory computer-readable medium of claim 1, the operations further comprising:
- transmitting a user query, the user query comprising an identification of a position within the storyboard the user query was created;
- presenting the position within the storyboard the user query was created in response to a request to access to the user query; and
- transmitting a response to the user query in response to user input.
3. The non-transitory computer-readable medium of claim 1, the operations further comprising:
- storing user query data;
- determining a plurality of variables associated with user interaction with the frames; and
- determining analytic data based on the variables, the analytic data defining a level of interaction with the frames.
4. The non-transitory computer-readable medium of claim 3, the operations further comprising generating a report based on the analytic data.
5. The non-transitory computer-readable medium of claim 4, wherein the report based on the analytic data includes information defining a level of effort by a student, a level of comprehension of the student, effort trends by the student, a learning objective the student should focus on based on a number of likes associated with the learning objective, a learning objective the student should focus on based on performance of the student as to the leaning objective, or combinations thereof.
6. The non-transitory computer-readable medium of claim 4, wherein the report based on the analytic data includes information defining a number of questions presented by the student, a number of annotations to the storyboard by the student, a ranking of learning objectives most misunderstood by the student, a ranking of which questions are most misunderstood by the student, a ranking of which learning objectives are associated with the most questions, a ranking of students that require support based on performance, or combinations thereof.
7. The non-transitory computer-readable medium of claim 4, wherein:
- the analytic data defines interactions with at least one question presented at the frames; and
- the operations further comprise generating the report based on the analytic data comprises a review sheet of the frames specific to a first interactions with the frames from a first client device.
8. The non-transitory computer-readable medium of claim 4, wherein:
- the analytic data defines interactions with at least one question presented at the frames; and
- the operations further comprise generating the report based on the analytic data comprises a ranking of the interactions with the at least one question.
9. A method comprising:
- displaying a storyboard via a user output device, the story board comprising: a plurality of frames, the frames comprising an illustration, the illustration comprising a first state and a second state; and
- changing the illustration within the frame from the first state to the second state based on a scroll command from a user input device from a first frame to a second frame of the plurality of frames.
10. The method claim 9, further comprising:
- transmitting a user query, the user query comprising an identification of a position within the storyboard the user query was created;
- presenting the position within the storyboard the user query was created in response to a request to access to the user query; and
- transmitting a response to the user query in response to user input.
11. The method of claim 9, further comprising:
- storing user query data;
- determining a plurality of variables associated with user interaction with the frames; and
- determining analytic data based on the variables, the analytic data defining a level of interaction with the frames.
12. The method of claim 11, further comprising generating a report based on the analytic data.
13. The method of claim 12, wherein the report based on the analytic data includes information defining a level of effort by a student, a level of comprehension of the student, effort trends by the student, a learning objective the student should focus on based on a number of likes associated with the learning objective, a learning objective the student should focus on based on performance of the student as to the leaning objective, or combinations thereof.
14. The method of claim 12, wherein the report based on the analytic data includes information defining a number of questions presented by the student, a number of annotations to the storyboard by the student, a ranking of learning objectives most misunderstood by the student, a ranking of which questions are most misunderstood by the student, a ranking of which learning objectives are associated with the most questions, a ranking of students that require support based on performance, or combinations thereof.
15. The method of claim 12, wherein:
- the analytic data defines interactions with at least one question presented at the frames; and
- further comprising generating the report based on the analytic data comprises a review sheet of the frames specific to a first interactions with the frames from a first client device.
16. The method of claim 12, wherein:
- the analytic data defines interactions with at least one question presented at the frames; and
- further comprising generating the report based on the analytic data comprises a ranking of the interactions with the at least one question.
17. A system comprising:
- a processor; and
- a non-transitory computer-readable media storing instructions that, when executed by the processor, causes the processor to perform operations comprising: displaying a storyboard via a user output device, the story board comprising: a plurality of frames, the frames comprising an illustration, the illustration comprising a first state and a second state; changing the illustration within the frame from the first state to the second state based on a scroll command from a user input device from a first frame to a second frame of the plurality of frames; transmitting a user query, the user query comprising an identification of a position within the storyboard the user query was created; presenting the position within the storyboard the user query was created in response to a request to access to the user query; and transmitting a response to the user query in response to user input.
18. The system of claim 17, the operations further comprising:
- transmitting a user query, the user query comprising an identification of a position within the storyboard the user query was created;
- presenting the position within the storyboard the user query was created in response to a request to access to the user query; and
- transmitting a response to the user query in response to user input.
19. The system of claim 1, the operations further comprising:
- storing user query data;
- determining a plurality of variables associated with user interaction with the frames; and
- determining analytic data based on the variables, the analytic data defining a level of interaction with the frames.
20. The system of claim 3, the operations further comprising generating a report based on the analytic data.
Type: Application
Filed: Jan 28, 2022
Publication Date: Jul 28, 2022
Inventor: Sina Azizi (San Diego, CA)
Application Number: 17/588,153